---------------------------------------------------------------------- This is the API documentation for the pharmadata library. ---------------------------------------------------------------------- ## Dataclasses Data-holding classes DatasetMeta(dataset: 'str', collection: 'str', file_label: 'str | None', structure: 'str | None', number_rows: 'int', column_names: 'tuple[str, ...]', column_labels: 'tuple[str | None, ...]', column_types: 'tuple[str | None, ...]', column_mandatory: 'tuple[str | None, ...]', column_roles: 'tuple[str | None, ...]') -> None Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) ## Functions Public functions get_output_format() -> 'OutputFormat' Return the current dataset output format. Context-local: the one set in this thread or asyncio task, or the default ``"polars"``. Returns ------- OutputFormat ``"arrow"``, ``"polars"`` (the default) or ``"pandas"``. Examples -------- >>> pharmadata.get_output_format() 'polars' set_output_arrow() -> 'None' Return datasets and metadata as pyarrow Tables for the current context. This is the zero-copy format: the shipped parquet is read into an immutable ``pyarrow.Table``, which is what the ``"arrow"`` output hands back directly. Notes ----- Context-local: applies only to the current thread or asyncio task. Examples -------- >>> pharmadata.set_output_arrow() >>> tbl = pharmadata.pharmaverseadam.adsl >>> type(tbl).__module__.split(".")[0] 'pyarrow' >>> pharmadata.set_output_polars() # restore the default set_output_pandas() -> 'None' Return dataset attributes as pandas DataFrames for the current context. See :func:`set_output_polars` for the context-locality notes. Examples -------- >>> pharmadata.set_output_pandas() >>> df = pharmadata.pharmaverseadam.adsl >>> type(df).__module__.split(".")[0] 'pandas' >>> pharmadata.set_output_polars() # restore the default set_output_polars() -> 'None' Return dataset attributes as polars DataFrames for the current context. This is the default output format. Call :func:`set_output_pandas` to switch. Notes ----- Context-local: applies only to the current thread or asyncio task. Examples -------- >>> pharmadata.set_output_pandas() >>> df = pharmadata.pharmaverseadam.adsl >>> type(df).__module__.split(".")[0] 'pandas' >>> pharmadata.set_output_polars() >>> pharmadata.get_output_format() 'polars' use_output_format(name: 'OutputFormat') -> 'Generator[None, None, None]' Use *name* as the dataset output format for a ``with`` block. The previous format is restored on exit, including when the block raises. The switch is context-local. Parameters ---------- name : OutputFormat The format to use inside the block: ``"arrow"``, ``"polars"`` or ``"pandas"``. Raises ------ ValueError If *name* is not ``"arrow"``, ``"polars"`` or ``"pandas"``. Examples -------- >>> with pharmadata.output_format("pandas"): ... df = pharmadata.pharmaverseadam.adsl ... type(df).__module__.split(".")[0] 'pandas' >>> pharmadata.get_output_format() # restored on exit 'polars' build(collection: 'str', name: 'str') -> 'DatasetMeta' The DatasetMeta of one dataset, built once and shared process-wide. list_datasets() -> 'list[str]' Names of the available SDTM datasets, sorted alphabetically. Returns ------- list[str] A list of dataset names. Examples -------- >>> "dm" in cdiscpilotsdtm.list_datasets() True meta(name: 'str') -> 'DatasetMeta' pyreadstat-style metadata of a dataset. Parameters ---------- name : str The dataset name, e.g. ``"dm"``. Returns ------- DatasetMeta The metadata object the ``_meta`` module attribute serves. Raises ------ ValueError If *name* is not a known SDTM dataset. Examples -------- >>> cdiscpilotsdtm.meta("dm").column_names_to_labels["STUDYID"] 'Study Identifier' meta_tables() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Dataset-level metadata: one row per dataset. Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per dataset, in the active output format, with the columns ``dataset, label, n_rows, n_cols``. Examples -------- >>> cdiscpilotsdtm.meta_tables().columns ['dataset', 'label', 'n_rows', 'n_cols'] meta_columns() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Column-level metadata of every SDTM dataset (long format). Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per column of every dataset, in the active output format, with the columns ``dataset, variable, label, type``. Examples -------- >>> cdiscpilotsdtm.meta_columns().columns ['dataset', 'variable', 'label', 'type'] meta_specs() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Column-level specifications of every SDTM dataset (long format). Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per variable, in the active output format, with the columns ``dataset, variable, label, type, mandatory, role``. Examples -------- >>> cdiscpilotsdtm.meta_specs().columns ['dataset', 'variable', 'label', 'type', 'mandatory', 'role'] to_dict() -> 'dict[str, pa.Table | pl.DataFrame | pd.DataFrame]' Every SDTM dataset loaded at once, keyed by name. Reads the whole collection, so prefer the lazy attributes (e.g. ``cdiscpilotsdtm.dm``) when only a few datasets are needed. Honors the active output format: with ``output_format="pandas"`` the values are pandas DataFrames. Returns ------- dict[str, pa.Table | pl.DataFrame | pd.DataFrame] One entry per dataset, mapping each dataset name to its frame in the active output format. Examples -------- >>> "dm" in cdiscpilotsdtm.to_dict() True build(collection: 'str', name: 'str') -> 'DatasetMeta' The DatasetMeta of one dataset, built once and shared process-wide. list_datasets() -> 'list[str]' Names of the available SDTM datasets, sorted alphabetically. Returns ------- list[str] A list of dataset names. Examples -------- >>> "dm" in pharmaversesdtm.list_datasets() True meta(name: 'str') -> 'DatasetMeta' pyreadstat-style metadata of a dataset. Parameters ---------- name : str The dataset name, e.g. ``"dm"``. Returns ------- DatasetMeta The metadata object the ``_meta`` module attribute serves. Raises ------ ValueError If *name* is not a known SDTM dataset. Examples -------- >>> pharmaversesdtm.meta("dm").column_names_to_labels["STUDYID"] 'Study Identifier' meta_tables() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Dataset-level metadata: one row per dataset. Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per dataset, in the active output format, with the columns ``dataset, label, n_rows, n_cols``. Examples -------- >>> pharmaversesdtm.meta_tables().columns ['dataset', 'label', 'n_rows', 'n_cols'] meta_columns() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Column-level metadata of every SDTM dataset (long format). Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per column of every dataset, in the active output format, with the columns ``dataset, variable, label, type``. Examples -------- >>> pharmaversesdtm.meta_columns().columns ['dataset', 'variable', 'label', 'type'] meta_specs() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Column-level specifications of every SDTM dataset (long format). Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per variable, in the active output format, with the columns ``dataset, variable, label, type, mandatory, role``. Examples -------- >>> pharmaversesdtm.meta_specs().columns ['dataset', 'variable', 'label', 'type', 'mandatory', 'role'] to_dict() -> 'dict[str, pa.Table | pl.DataFrame | pd.DataFrame]' Every SDTM dataset loaded at once, keyed by name. Reads the whole collection, so prefer the lazy attributes (e.g. ``pharmaversesdtm.dm``) when only a few datasets are needed. Honors the active output format: with ``output_format="pandas"`` the values are pandas DataFrames. Returns ------- dict[str, pa.Table | pl.DataFrame | pd.DataFrame] One entry per dataset, mapping each dataset name to its frame in the active output format. Examples -------- >>> "dm" in pharmaversesdtm.to_dict() True build(collection: 'str', name: 'str') -> 'DatasetMeta' The DatasetMeta of one dataset, built once and shared process-wide. list_datasets() -> 'list[str]' Names of the available ADaM datasets, sorted alphabetically. Returns ------- list[str] A list of dataset names. Examples -------- >>> "adsl" in cdiscpilotadam.list_datasets() True meta(name: 'str') -> 'DatasetMeta' pyreadstat-style metadata of a dataset. Parameters ---------- name : str The dataset name, e.g. ``"adsl"``. Returns ------- DatasetMeta The metadata object the ``_meta`` module attribute serves. Raises ------ ValueError If *name* is not a known ADaM dataset. Examples -------- >>> cdiscpilotadam.meta("adsl").column_names_to_labels["STUDYID"] 'Study Identifier' meta_tables() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Dataset-level metadata: one row per dataset. Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per dataset, in the active output format, with the columns ``dataset, label, n_rows, n_cols``. Examples -------- >>> cdiscpilotadam.meta_tables().columns ['dataset', 'label', 'n_rows', 'n_cols'] meta_columns() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Column-level metadata of every ADaM dataset (long format). Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per column of every dataset, in the active output format, with the columns ``dataset, variable, label, type``. Examples -------- >>> cdiscpilotadam.meta_columns().columns ['dataset', 'variable', 'label', 'type'] meta_specs() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Column-level specifications of every ADaM dataset (long format). Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per variable, in the active output format, with the columns ``dataset, variable, label, type, mandatory, role``. Examples -------- >>> cdiscpilotadam.meta_specs().columns ['dataset', 'variable', 'label', 'type', 'mandatory', 'role'] to_dict() -> 'dict[str, pa.Table | pl.DataFrame | pd.DataFrame]' Every ADaM dataset loaded at once, keyed by name. Reads the whole collection, so prefer the lazy attributes (e.g. ``cdiscpilotadam.adsl``) when only a few datasets are needed. Honors the active output format: with ``output_format="pandas"`` the values are pandas DataFrames. Returns ------- dict[str, pa.Table | pl.DataFrame | pd.DataFrame] One entry per dataset, mapping each dataset name to its frame in the active output format. Examples -------- >>> "adsl" in cdiscpilotadam.to_dict() True build(collection: 'str', name: 'str') -> 'DatasetMeta' The DatasetMeta of one dataset, built once and shared process-wide. list_datasets() -> 'list[str]' Names of the available ADaM datasets, sorted alphabetically. Returns ------- list[str] A list of dataset names. Examples -------- >>> "adsl" in pharmaverseadam.list_datasets() True meta(name: 'str') -> 'DatasetMeta' pyreadstat-style metadata of a dataset. Parameters ---------- name : str The dataset name, e.g. ``"adsl"``. Returns ------- DatasetMeta The metadata object the ``_meta`` module attribute serves. Raises ------ ValueError If *name* is not a known ADaM dataset. Examples -------- >>> pharmaverseadam.meta("adsl").column_names_to_labels["STUDYID"] 'Study Identifier' meta_tables() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Dataset-level metadata: one row per dataset. Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per dataset, in the active output format, with the columns ``dataset, label, n_rows, n_cols``. Examples -------- >>> pharmaverseadam.meta_tables().columns ['dataset', 'label', 'n_rows', 'n_cols'] meta_columns() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Column-level metadata of every ADaM dataset (long format). Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per column of every dataset, in the active output format, with the columns ``dataset, variable, label, type``. Examples -------- >>> pharmaverseadam.meta_columns().columns ['dataset', 'variable', 'label', 'type'] meta_specs() -> 'pa.Table | pl.DataFrame | pd.DataFrame' Column-level specifications of every ADaM dataset (long format). Returns ------- pa.Table or pl.DataFrame or pd.DataFrame One row per variable, in the active output format, with the columns ``dataset, variable, label, type, mandatory, role``. Examples -------- >>> pharmaverseadam.meta_specs().columns ['dataset', 'variable', 'label', 'type', 'mandatory', 'role'] to_dict() -> 'dict[str, pa.Table | pl.DataFrame | pd.DataFrame]' Every ADaM dataset loaded at once, keyed by name. Reads the whole collection, so prefer the lazy attributes (e.g. ``pharmaverseadam.adsl``) when only a few datasets are needed. Honors the active output format: with ``output_format="pandas"`` the values are pandas DataFrames. Returns ------- dict[str, pa.Table | pl.DataFrame | pd.DataFrame] One entry per dataset, mapping each dataset name to its frame in the active output format. Examples -------- >>> "adsl" in pharmaverseadam.to_dict() True ## Constants Module-level constants and data cdiscpilotsdtm.ae ae - Adverse Events SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 961 rows x 37 columns. Structure: One record per adverse event per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier AESEQ (Float64): Sequence Number AESPID (String): Sponsor-Defined Identifier AETERM (String): Reported Term for the Adverse Event AELLT (String): Lowest Level Term AELLTCD (Float64): Lowest Level Term Code AEDECOD (String): Dictionary-Derived Term AEPTCD (Float64): Preferred Term Code AEHLT (String): High Level Term AEHLTCD (Float64): High Level Term Code AEHLGT (String): High Level Group Term AEHLGTCD (Float64): High Level Group Term Code AEBODSYS (String): Body System or Organ Class AEBDSYCD (Float64): Body System or Organ Class Code AESOC (String): Primary System Organ Class AESOCCD (Float64): Primary System Organ Class Code AESEV (String): Severity/Intensity AESER (String): Serious Event AEACN (String): Action Taken with Study Treatment AEREL (String): Causality AEOUT (String): Outcome of Adverse Event AESCAN (String): Involves Cancer AESCONG (String): Congenital Anomaly or Birth Defect AESDISAB (String): Persist or Signif Disability/Incapacity AESDTH (String): Results in Death AESHOSP (String): Requires or Prolongs Hospitalization AESLIFE (String): Is Life Threatening AESOD (String): Occurred with Overdose EPOCH (String): Epoch AEDTC (String): Date/Time of Collection AESTDTC (String): Start Date/Time of Adverse Event AEENDTC (String): End Date/Time of Adverse Event AEDY (Float64): Study Day of Visit/Collection/Exam AESTDY (Float64): Study Day of Start of Adverse Event AEENDY (Float64): Study Day of End of Adverse Event cdiscpilotsdtm.ae_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.cm cm - Concomitant Medications SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 7510 rows x 23 columns. Structure: One record per recorded medication occurrence or constant-dosing interval per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier CMSEQ (Float64): Sequence Number CMSPID (String): Sponsor-Defined Identifier CMTRT (String): Reported Name of Drug, Med, or Therapy CMDECOD (String): Standardized Medication Name CMINDC (String): Indication CMCLAS (String): Medication Class CMDOSE (Float64): Dose per Administration CMDOSU (String): Dose Units CMDOSFRQ (String): Dosing Frequency per Interval CMROUTE (String): Route of Administration VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch CMDTC (String): Date/Time of Collection CMSTDTC (String): Start Date/Time of Medication CMENDTC (String): End Date/Time of Medication CMDY (Float64): Study Day of Visit/Collection/Exam CMSTDY (Float64): Study Day of Start of Medication CMENDY (Float64): Study Day of End of Medication cdiscpilotsdtm.cm_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.dm dm - Demographics SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 306 rows x 25 columns. Structure: One record per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFICDTC (String): Date/Time of Informed Consent RFPENDTC (String): Date/Time of End of Participation DTHDTC (String): Date/Time of Death DTHFL (String): Subject Death Flag SITEID (String): Study Site Identifier AGE (Float64): Age AGEU (String): Age Units SEX (String): Sex RACE (String): Race ETHNIC (String): Ethnicity ARMCD (String): Planned Arm Code ARM (String): Description of Planned Arm ACTARMCD (String): Actual Arm Code ACTARM (String): Description of Actual Arm COUNTRY (String): Country DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection cdiscpilotsdtm.dm_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.ds ds - Disposition SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 596 rows x 15 columns. Structure: One record per disposition status or protocol milestone per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier DSSEQ (Float64): Sequence Number DSSPID (String): Sponsor-Defined Identifier DSTERM (String): Reported Term for the Disposition Event DSDECOD (String): Standardized Disposition Term DSCAT (String): Category for Disposition Event VISITNUM (Float64): Visit Number VISIT (String): Visit Name EPOCH (String): Epoch DSDTC (String): Date/Time of Collection DSSTDTC (String): Start Date/Time of Disposition Event DSDY (Float64): Study Day of Visit/Collection/Exam DSSTDY (Float64): Study Day of Start of Disposition Event cdiscpilotsdtm.ds_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.ex ex - Exposure SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 591 rows x 18 columns. Structure: One record per constant dosing interval per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier EXSEQ (Float64): Sequence Number EXTRT (String): Name of Treatment EXDOSE (Float64): Dose EXDOSU (String): Dose Units EXDOSFRM (String): Dose Form EXDOSFRQ (String): Dosing Frequency per Interval EXROUTE (String): Route of Administration VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch EXSTDTC (String): Start Date/Time of Treatment EXENDTC (String): End Date/Time of Treatment EXSTDY (Float64): Study Day of Start of Treatment EXENDY (Float64): Study Day of End of Treatment cdiscpilotsdtm.ex_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.lbch lbch - Laboratory Tests Results SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 32740 rows x 24 columns. Structure: One record per analyte per planned time point number per time point reference per visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier LBSEQ (Float64): Sequence Number LBTESTCD (String): Lab Test or Examination Short Name LBTEST (String): Lab Test or Examination Name LBCAT (String): Category for Lab Test LBORRES (String): Result or Finding in Original Units LBORRESU (String): Original Units LBORNRLO (String): Reference Range Lower Limit in Orig Unit LBORNRHI (String): Reference Range Upper Limit in Orig Unit LBSTRESC (String): Character Result/Finding in Std Format LBSTRESN (Float64): Numeric Result/Finding in Standard Units LBSTRESU (String): Standard Units LBSTNRLO (Float64): Reference Range Lower Limit-Std Units LBSTNRHI (Float64): Reference Range Upper Limit-Std Units LBNRIND (String): Reference Range Indicator LBBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch LBDTC (String): Date/Time of Specimen Collection LBDY (Float64): Study Day of Specimen Collection cdiscpilotsdtm.lbch_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.lbhe lbhe - Laboratory Tests Results SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 21927 rows x 24 columns. Structure: One record per analyte per planned time point number per time point reference per visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier LBSEQ (Float64): Sequence Number LBTESTCD (String): Lab Test or Examination Short Name LBTEST (String): Lab Test or Examination Name LBCAT (String): Category for Lab Test LBORRES (String): Result or Finding in Original Units LBORRESU (String): Original Units LBORNRLO (String): Reference Range Lower Limit in Orig Unit LBORNRHI (String): Reference Range Upper Limit in Orig Unit LBSTRESC (String): Character Result/Finding in Std Format LBSTRESN (Float64): Numeric Result/Finding in Standard Units LBSTRESU (String): Standard Units LBSTNRLO (Float64): Reference Range Lower Limit-Std Units LBSTNRHI (Float64): Reference Range Upper Limit-Std Units LBNRIND (String): Reference Range Indicator LBBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch LBDTC (String): Date/Time of Specimen Collection LBDY (Float64): Study Day of Specimen Collection cdiscpilotsdtm.lbhe_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.lbur lbur - Laboratory Tests Results SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 4913 rows x 24 columns. Structure: One record per analyte per planned time point number per time point reference per visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier LBSEQ (Float64): Sequence Number LBTESTCD (String): Lab Test or Examination Short Name LBTEST (String): Lab Test or Examination Name LBCAT (String): Category for Lab Test LBORRES (String): Result or Finding in Original Units LBORRESU (String): Original Units LBORNRLO (String): Reference Range Lower Limit in Orig Unit LBORNRHI (String): Reference Range Upper Limit in Orig Unit LBSTRESC (String): Character Result/Finding in Std Format LBSTRESN (Float64): Numeric Result/Finding in Standard Units LBSTRESU (String): Standard Units LBSTNRLO (Float64): Reference Range Lower Limit-Std Units LBSTNRHI (Float64): Reference Range Upper Limit-Std Units LBNRIND (String): Reference Range Indicator LBBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch LBDTC (String): Date/Time of Specimen Collection LBDY (Float64): Study Day of Specimen Collection cdiscpilotsdtm.lbur_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.mh mh - Medical History SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 1817 rows x 19 columns. Structure: One record per medical history event per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier MHSEQ (Float64): Sequence Number MHSPID (String): Sponsor-Defined Identifier MHTERM (String): Reported Term for the Medical History MHLLT (String): Lowest Level Term MHDECOD (String): Dictionary-Derived Term MHHLT (String): High Level Term MHHLGT (String): High Level Group Term MHCAT (String): Category for Medical History MHBODSYS (String): Body System or Organ Class MHSEV (String): Severity/Intensity VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit MHDTC (String): Date/Time of History Collection MHSTDTC (String): Start Date/Time of Medical History Event MHDY (Float64): Study Day of History Collection cdiscpilotsdtm.mh_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.qsco qsco - Questionnaires SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 12241 rows x 23 columns. Structure: One record per questionnaire per question per time point per visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier QSSEQ (Float64): Sequence Number QSTESTCD (String): Question Short Name QSTEST (String): Question Name QSCAT (String): Category of Question QSSCAT (String): Subcategory for Question QSORRES (String): Finding in Original Units QSORRESU (String): Original Units QSSTRESC (String): Result or Finding in Standard Format QSSTRESN (Float64): Numeric Finding in Standard Units QSSTRESU (String): Standard Units QSSTAT (String): Completion Status QSREASND (String): Reason Not Performed QSBLFL (String): Baseline Flag QSDRVFL (String): Derived Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch QSDTC (String): Date/Time of Finding QSDY (Float64): Study Day of Finding cdiscpilotsdtm.qsco_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.qsda qsda - Questionnaires SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 32920 rows x 23 columns. Structure: One record per questionnaire per question per time point per visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier QSSEQ (Float64): Sequence Number QSTESTCD (String): Question Short Name QSTEST (String): Question Name QSCAT (String): Category of Question QSSCAT (String): Subcategory for Question QSORRES (String): Finding in Original Units QSORRESU (String): Original Units QSSTRESC (String): Result or Finding in Standard Format QSSTRESN (Float64): Numeric Finding in Standard Units QSSTRESU (String): Standard Units QSSTAT (String): Completion Status QSREASND (String): Reason Not Performed QSBLFL (String): Baseline Flag QSDRVFL (String): Derived Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch QSDTC (String): Date/Time of Finding QSDY (Float64): Study Day of Finding cdiscpilotsdtm.qsda_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.qsgi qsgi - Questionnaires SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 562 rows x 23 columns. Structure: One record per questionnaire per question per time point per visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier QSSEQ (Float64): Sequence Number QSTESTCD (String): Question Short Name QSTEST (String): Question Name QSCAT (String): Category of Question QSSCAT (String): Subcategory for Question QSORRES (String): Finding in Original Units QSORRESU (String): Original Units QSSTRESC (String): Result or Finding in Standard Format QSSTRESN (Float64): Numeric Finding in Standard Units QSSTRESU (String): Standard Units QSSTAT (String): Completion Status QSREASND (String): Reason Not Performed QSBLFL (String): Baseline Flag QSDRVFL (String): Derived Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch QSDTC (String): Date/Time of Finding QSDY (Float64): Study Day of Finding cdiscpilotsdtm.qsgi_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.qshi qshi - Questionnaires SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 3302 rows x 23 columns. Structure: One record per questionnaire per question per time point per visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier QSSEQ (Float64): Sequence Number QSTESTCD (String): Question Short Name QSTEST (String): Question Name QSCAT (String): Category of Question QSSCAT (String): Subcategory for Question QSORRES (String): Finding in Original Units QSORRESU (String): Original Units QSSTRESC (String): Result or Finding in Standard Format QSSTRESN (Float64): Numeric Finding in Standard Units QSSTRESU (String): Standard Units QSSTAT (String): Completion Status QSREASND (String): Reason Not Performed QSBLFL (String): Baseline Flag QSDRVFL (String): Derived Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch QSDTC (String): Date/Time of Finding QSDY (Float64): Study Day of Finding cdiscpilotsdtm.qshi_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.qsmm qsmm - Questionnaires SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 1524 rows x 23 columns. Structure: One record per questionnaire per question per time point per visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier QSSEQ (Float64): Sequence Number QSTESTCD (String): Question Short Name QSTEST (String): Question Name QSCAT (String): Category of Question QSSCAT (String): Subcategory for Question QSORRES (String): Finding in Original Units QSORRESU (String): Original Units QSSTRESC (String): Result or Finding in Standard Format QSSTRESN (Float64): Numeric Finding in Standard Units QSSTRESU (String): Standard Units QSSTAT (String): Completion Status QSREASND (String): Reason Not Performed QSBLFL (String): Baseline Flag QSDRVFL (String): Derived Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch QSDTC (String): Date/Time of Finding QSDY (Float64): Study Day of Finding cdiscpilotsdtm.qsmm_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.qsni qsni - Questionnaires SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 71200 rows x 23 columns. Structure: One record per questionnaire per question per time point per visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier QSSEQ (Float64): Sequence Number QSTESTCD (String): Question Short Name QSTEST (String): Question Name QSCAT (String): Category of Question QSSCAT (String): Subcategory for Question QSORRES (String): Finding in Original Units QSORRESU (String): Original Units QSSTRESC (String): Result or Finding in Standard Format QSSTRESN (Float64): Numeric Finding in Standard Units QSSTRESU (String): Standard Units QSSTAT (String): Completion Status QSREASND (String): Reason Not Performed QSBLFL (String): Baseline Flag QSDRVFL (String): Derived Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch QSDTC (String): Date/Time of Finding QSDY (Float64): Study Day of Finding cdiscpilotsdtm.qsni_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.relrec relrec - Related Records SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 211 rows x 7 columns. Structure: One record per related record, group of records or datasets. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value RELTYPE (String): Relationship Type RELID (String): Relationship Identifier cdiscpilotsdtm.relrec_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.sc sc - Subject Characteristics SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 254 rows x 14 columns. Structure: One record per characteristic per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier SCSEQ (Float64): Sequence Number SCTESTCD (String): Subject Characteristic Short Name SCTEST (String): Subject Characteristic SCCAT (String): Category for Subject Characteristic SCORRES (String): Result or Finding in Original Units SCORRESU (String): Original Units SCSTRESC (String): Character Result/Finding in Std Format SCSTRESN (Float64): Numeric Result/Finding in Standard Units SCSTRESU (String): Standard Units SCDTC (String): Date/Time of Collection SCDY (Float64): Study Day of Examination cdiscpilotsdtm.sc_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.se se - Subject Elements SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 752 rows x 12 columns. Structure: One record per actual Element per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier SESEQ (Float64): Sequence Number ETCD (String): Element Code ELEMENT (String): Description of Element SEUPDES (String): Description of Unplanned Element EPOCH (String): Epoch SESTDTC (String): Start Date/Time of Element SEENDTC (String): End Date/Time of Element SESTDY (Float64): Study Day of Start of Observation SEENDY (Float64): Study Day of End of Observation cdiscpilotsdtm.se_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.suppae suppae - Supplemental Qualifiers for AE SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 961 rows x 10 columns. Structure: One record per IDVAR, IDVARVAL, and QNAM value per subject. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin QEVAL (String): Evaluator cdiscpilotsdtm.suppae_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.suppdm suppdm - Supplemental Qualifiers for DM SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 1197 rows x 10 columns. Structure: One record per IDVAR, IDVARVAL, and QNAM value per subject. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin QEVAL (String): Evaluator cdiscpilotsdtm.suppdm_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.suppds suppds - Supplemental Qualifiers for DS SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 3 rows x 10 columns. Structure: One record per IDVAR, IDVARVAL, and QNAM value per subject. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin QEVAL (String): Evaluator cdiscpilotsdtm.suppds_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.supplbch supplbch - Supplemental Qualifiers for LB SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 37124 rows x 10 columns. Structure: One record per IDVAR, IDVARVAL, and QNAM value per subject. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin QEVAL (String): Evaluator cdiscpilotsdtm.supplbch_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.supplbhe supplbhe - Supplemental Qualifiers for LB SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 24558 rows x 10 columns. Structure: One record per IDVAR, IDVARVAL, and QNAM value per subject. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin QEVAL (String): Evaluator cdiscpilotsdtm.supplbhe_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.supplbur supplbur - Supplemental Qualifiers for LB SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 2721 rows x 10 columns. Structure: One record per IDVAR, IDVARVAL, and QNAM value per subject. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin QEVAL (String): Evaluator cdiscpilotsdtm.supplbur_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.sv sv - Subject Visits SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 3559 rows x 12 columns. Structure: One record per actual visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch SVSTDTC (String): Start Date/Time of Visit SVENDTC (String): End Date/Time of Visit SVSTDY (Float64): Study Day of Start of Visit SVENDY (Float64): Study Day of End of Visit SVUPDES (String): Description of Unplanned Visit cdiscpilotsdtm.sv_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.ta ta - Trial Arms SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 11 rows x 10 columns. Structure: One record per planned Element per Arm. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation ARMCD (String): Planned Arm Code ARM (String): Description of Planned Arm TAETORD (Float64): Planned Order of Element within Arm ETCD (String): Element Code ELEMENT (String): Description of Element TABRANCH (String): Branch TATRANS (String): Transition Rule EPOCH (String): Epoch cdiscpilotsdtm.ta_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.te te - Trial Elements SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 7 rows x 7 columns. Structure: One record per planned Element. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation ETCD (String): Element Code ELEMENT (String): Description of Element TESTRL (String): Rule for Start of Element TEENRL (String): Rule for End of Element TEDUR (String): Planned Duration of Element cdiscpilotsdtm.te_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.ti ti - Trial Inclusion/ Exclusion Criteria SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 31 rows x 5 columns. Structure: One record per I/E criterion. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation IETESTCD (String): Inclusion/Exclusion Criterion Short Name IETEST (String): Inclusion/Exclusion Criterion IECAT (String): Inclusion/Exclusion Category cdiscpilotsdtm.ti_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.ts ts - Trial Summary SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 48 rows x 10 columns. Structure: One record per trial summary parameter value. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation TSSEQ (Float64): Sequence Number TSPARMCD (String): Trial Summary Parameter Short Name TSPARM (String): Trial Summary Parameter TSVAL (String): Parameter Value TSVALNF (String): Parameter Null Flavor TSVALCD (String): Parameter Value Code TSVCDREF (String): Name of the Reference Terminology TSVCDVER (String): Version of the Reference Terminology cdiscpilotsdtm.ts_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.tv tv - Trial Visits SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 21 rows x 8 columns. Structure: One record per planned Visit per Arm. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit ARMCD (String): Planned Arm Code TVSTRL (String): Visit Start Rule TVENRL (String): Visit End Rule cdiscpilotsdtm.tv_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotsdtm.vs vs - Vital Signs SDTM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 29643 rows x 25 columns. Structure: One record per vital sign measurement per time point per visit per subject. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier VSSEQ (Float64): Sequence Number VSTESTCD (String): Vital Signs Test Short Name VSTEST (String): Vital Signs Test Name VSPOS (String): Vital Signs Position of Subject VSORRES (String): Result or Finding in Original Units VSORRESU (String): Original Units VSSTRESC (String): Character Result/Finding in Std Format VSSTRESN (Float64): Numeric Result/Finding in Standard Units VSSTRESU (String): Standard Units VSSTAT (String): Completion Status VSLOC (String): Location of Vital Signs Measurement VSBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch VSDTC (String): Date/Time of Measurements VSDY (Float64): Study Day of Vital Signs VSTPT (String): Planned Time Point Name VSTPTNUM (Float64): Planned Time Point Number VSELTM (String): Planned Elapsed Time from Time Point Ref VSTPTREF (String): Time Point Reference cdiscpilotsdtm.vs_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.ae ae - Adverse Events SDTM (pharmaverse), from pharmaversesdtm (). 1191 rows x 35 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier AESEQ (Float64): Sequence Number AESPID (String): Sponsor-Defined Identifier AETERM (String): Reported Term for the Adverse Event AELLT (String): Lowest Level Term AELLTCD (Float64): Lowest Level Term Code AEDECOD (String): Dictionary-Derived Term AEPTCD (Float64): Preferred Term Code AEHLT (String): High Level Term AEHLTCD (Float64): High Level Term Code AEHLGT (String): High Level Group Term AEHLGTCD (Float64): High Level Group Term Code AEBODSYS (String): Body System or Organ Class AEBDSYCD (Float64): Body System or Organ Class Code AESOC (String): Primary System Organ Class AESOCCD (Float64): Primary System Organ Class Code AESEV (String): Severity/Intensity AESER (String): Serious Event AEACN (String): Action Taken with Study Treatment AEREL (String): Causality AEOUT (String): Outcome of Adverse Event AESCAN (String): Involves Cancer AESCONG (String): Congenital Anomaly or Birth Defect AESDISAB (String): Persist or Signif Disability/Incapacity AESDTH (String): Results in Death AESHOSP (String): Requires or Prolongs Hospitalization AESLIFE (String): Is Life Threatening AESOD (String): Occurred with Overdose AEDTC (String): Date/Time of Collection AESTDTC (String): Start Date/Time of Adverse Event AEENDTC (String): End Date/Time of Adverse Event AESTDY (Float64): Study Day of Start of Adverse Event AEENDY (Float64): Study Day of End of Adverse Event pharmaversesdtm.ae_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.ae_ophtha ae_ophtha - Adverse Events for Ophthalmology SDTM (pharmaverse), from pharmaversesdtm (). 1191 rows x 37 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier AESEQ (Float64): Sequence Number AESPID (String): Sponsor-Defined Identifier AETERM (String): Reported Term for the Adverse Event AELLT (String): Lowest Level Term AELLTCD (Float64): Lowest Level Term Code AEDECOD (String): Dictionary-Derived Term AEPTCD (Float64): Preferred Term Code AEHLT (String): High Level Term AEHLTCD (Float64): High Level Term Code AEHLGT (String): High Level Group Term AEHLGTCD (Float64): High Level Group Term Code AEBODSYS (String): Body System or Organ Class AEBDSYCD (Float64): Body System or Organ Class Code AESOC (String): Primary System Organ Class AESOCCD (Float64): Primary System Organ Class Code AESEV (String): Severity/Intensity AESER (String): Serious Event AEACN (String): Action Taken with Study Treatment AEREL (String): Causality AEOUT (String): Outcome of Adverse Event AESCAN (String): Involves Cancer AESCONG (String): Congenital Anomaly or Birth Defect AESDISAB (String): Persist or Signif Disability/Incapacity AESDTH (String): Results in Death AESHOSP (String): Requires or Prolongs Hospitalization AESLIFE (String): Is Life Threatening AESOD (String): Occurred with Overdose AEDTC (String): Date/Time of Collection AESTDTC (String): Start Date/Time of Adverse Event AEENDTC (String): End Date/Time of Adverse Event AESTDY (Float64): Study Day of Start of Adverse Event AEENDY (Float64): Study Day of End of Adverse Event AELAT (String): Laterality AELOC (String): Location pharmaversesdtm.ae_ophtha_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.ag_neuro ag_neuro - Procedure Agents Dataset-neuro SDTM (pharmaverse), from pharmaversesdtm (). 68 rows x 13 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier AGSEQ (Int32): Sequence Number AGTRT (String): Reported Agent Name AGCAT (String): Category for Agent AGDOSE (String): Dose per Administration AGDOSEU (String): Dose Units AGROUTE (String): Route of Administration AGLNKID (Float64): Link ID VISITNUM (Float64): Visit Number VISIT (String): Visit Name AGSTDTC (String): Start Date/Time of Agent pharmaversesdtm.ag_neuro_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.be be - Biospecimen Events SDTM (pharmaverse), from pharmaversesdtm (). 43 rows x 13 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier BESEQ (Float64): Sequence Number BEREFID (String): Reference ID BELNKID (Boolean): Link Identifier BETERM (String): Reported Term for the Biospecimen Event BECAT (String): Category for Biospecimen Event BELOC (String): Anatomical Location of Event VISITNUM (Float64): Visit Number BEDTC (String): Date/Time of Specimen Collection BESTDTC (String): Start Date/Time of Biospecimen Event BEENDTC (String): End Date/Time of Biospecimen Event pharmaversesdtm.be_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.ce_vaccine ce_vaccine - Clinical Events for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 44 rows x 29 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier CESEQ (Float64): Sequence Number CELNKID (String): Link ID CELNKGRP (String): Link Group ID CETERM (String): Reported Term for the Clinical Event CEDECOD (String): Dictionary-Derived Term CELAT (String): Laterality of Location of Clinical Event CELOC (String): Location of Clinical Event CECAT (String): Category for Clinical Event CESCAT (String): Subcategory for Clinical Event CEPRESP (String): Clinical Event Pre-Specified CEOCCUR (String): Clinical Event Occurrence CESEV (String): Severity/Intensity CEREL (String): Causality CEOUT (String): Outcome of Clinical Event EPOCH (String): Epoch CEDTC (String): Date/Time of Event Collection CESTDTC (String): Start Date/Time of Clinical Event CEENDTC (String): End Date/Time of Clinical Event CEDUR (String): Duration of Clinical Event CETPT (String): Planned Time Point Name CETPTNUM (Float64): Planned Time Point Number CETPTREF (String): Time Point Reference CERFTDTC (String): Date/Time of Reference Time Point CEEVINTX (String): Evaluation Interval Text CESTAT (String): Completion Status CEREASND (String): Reason Clinical Event Not Collected pharmaversesdtm.ce_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.cm cm - Concomitant Medication SDTM (pharmaverse), from pharmaversesdtm (). 7510 rows x 22 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier CMSEQ (Float64): Sequence Number CMSPID (String): Sponsor-Defined Identifier CMTRT (String): Reported Name of Drug, Med, or Therapy CMDECOD (String): Standardized Medication Name CMINDC (String): Indication CMCLAS (String): Medication Class CMDOSE (Float64): Dose per Administration CMDOSU (String): Dose Units CMDOSFRQ (String): Dosing Frequency per Interval CMROUTE (String): Route of Administration VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit CMDTC (String): Date/Time of Collection CMSTDTC (String): Start Date/Time of Medication CMENDTC (String): End Date/Time of Medication CMSTDY (Float64): Study Day of Start of Medication CMENDY (Float64): Study Day of End of Medication CMENRTPT (String): End Relative to Reference Time Point pharmaversesdtm.cm_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.dm dm - Demography SDTM (pharmaverse), from pharmaversesdtm (). 306 rows x 28 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFICDTC (String): Date/Time of Informed Consent RFPENDTC (String): Date/Time of End of Participation DTHDTC (String): Date/Time of Death DTHFL (String): Subject Death Flag SITEID (String): Study Site Identifier BRTHDTC (String): Date/Time of Birth AGE (Float64): Age AGEU (String): Age Units SEX (String): Sex RACE (String): Race ETHNIC (String): Ethnicity ARMCD (String): Planned Arm Code ARM (String): Description of Planned Arm ACTARMCD (String): Actual Arm Code ACTARM (String): Description of Actual Arm COUNTRY (String): Country DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection ARMNRS (String): Reason Arm and/or Actual Arm is Null ACTARMUD (String): Description of Unplanned Actual Arm pharmaversesdtm.dm_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.dm_metabolic dm_metabolic - Demographic Dataset-metabolic SDTM (pharmaverse), from pharmaversesdtm (). 5 rows x 28 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFICDTC (String): Date/Time of Informed Consent RFPENDTC (String): Date/Time of End of Participation DTHDTC (String): Date/Time of Death DTHFL (String): Subject Death Flag SITEID (String): Study Site Identifier BRTHDTC (String): Date/Time of Birth AGE (Float64): Age AGEU (String): Age Units SEX (String): Sex RACE (String): Race ETHNIC (String): Ethnicity ARMCD (String): Planned Arm Code ARM (String): Description of Planned Arm ACTARMCD (String): Actual Arm Code ACTARM (String): Description of Actual Arm COUNTRY (String): Country DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection ARMNRS (String): Reason Arm and/or Actual Arm is Null ACTARMUD (String): Description of Unplanned Actual Arm pharmaversesdtm.dm_metabolic_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.dm_neuro dm_neuro - Demographic Dataset-neuro SDTM (pharmaverse), from pharmaversesdtm (). 15 rows x 28 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFICDTC (String): Date/Time of Informed Consent RFPENDTC (String): Date/Time of End of Participation DTHDTC (String): Date/Time of Death DTHFL (String): Subject Death Flag SITEID (String): Study Site Identifier BRTHDTC (String): Date/Time of Birth AGE (Float64): Age AGEU (String): Age Units SEX (String): Sex RACE (String): Race ETHNIC (String): Ethnicity ARMCD (String): Planned Arm Code ARM (String): Description of Planned Arm ACTARMCD (String): Actual Arm Code ACTARM (String): Description of Actual Arm COUNTRY (String): Country DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection ARMNRS (String): Reason Arm and/or Actual Arm is Null ACTARMUD (String): Description of Unplanned Actual Arm pharmaversesdtm.dm_neuro_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.dm_peds dm_peds - Demographic Dataset-pediatrics SDTM (pharmaverse), from pharmaversesdtm (). 5 rows x 28 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFICDTC (String): Date/Time of Informed Consent RFPENDTC (String): Date/Time of End of Participation DTHDTC (String): Date/Time of Death DTHFL (String): Subject Death Flag SITEID (String): Study Site Identifier BRTHDTC (String): Date/Time of Birth AGE (Float64): Age AGEU (String): Age Units SEX (String): Sex RACE (String): Race ETHNIC (String): Ethnicity ARMCD (String): Planned Arm Code ARM (String): Description of Planned Arm ACTARMCD (String): Actual Arm Code ACTARM (String): Description of Actual Arm COUNTRY (String): Country DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection ARMNRS (String): Reason Arm and/or Actual Arm is Null ACTARMUD (String): Description of Unplanned Actual Arm pharmaversesdtm.dm_peds_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.dm_vaccine dm_vaccine - Demographics for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 2 rows x 30 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFICDTC (String): Date/Time of Informed Consent RFPENDTC (String): Date/Time of End of Participation DTHDTC (String): Date/Time of Death DTHFL (String): Subject Death Flag SITEID (Float64): Study Site Identifier INVID (Float64): Investigator Identifier INVNAM (String): Investigator Name BRTHDTC (String): Date/Time of Birth AGE (Float64): Age AGEU (String): Age Units SEX (String): Sex RACE (String): Race ETHNIC (String): Ethnicity ARMCD (String): Planned Arm Code ARM (String): Description of Planned Arm ACTARMCD (String): Actual Arm Code ACTARM (String): Description of Actual Arm COUNTRY (String): Country DMDTC (String): Date/Time of Collection DMDY (Int32): Study Day of Collection ARMNRS (String): Reason Arm and/or Actual Arm is Null ACTARMUD (String): Description of Unplanned Actual Arm pharmaversesdtm.dm_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.ds ds - Disposition SDTM (pharmaverse), from pharmaversesdtm (). 850 rows x 13 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier DSSEQ (Int32): Sequence Number DSSPID (String): Sponsor-Defined Identifier DSTERM (String): Reported Term for the Disposition Event DSDECOD (String): Standardized Disposition Term DSCAT (String): Category for Disposition Event VISITNUM (Float64): Visit Number VISIT (String): Visit Name DSDTC (String): Date/Time of Collection DSSTDTC (String): Start Date/Time of Disposition Event DSSTDY (Float64): Study Day of Start of Disposition Event pharmaversesdtm.ds_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.eg eg - Electrocardiogram SDTM (pharmaverse), from pharmaversesdtm (). 26717 rows x 23 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier EGSEQ (Float64): Sequence Number EGTESTCD (String): ECG Test Short Name EGTEST (String): ECG Test Name EGORRES (String): Result or Finding in Original Units EGORRESU (String): Original Units EGSTRESC (String): Character Result/Finding in Std Format EGSTRESN (Float64): Numeric Result/Finding in Standard Units EGSTRESU (String): Standard Units EGSTAT (String): Completion Status EGLOC (String): Location of Vital Signs Measurement EGBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EGDTC (String): Date/Time of Measurements EGDY (Float64): Study Day of Vital Signs EGTPT (String): Planned Time Point Number EGTPTNUM (Float64): Time Point Number EGELTM (String): Planned Elapsed Time from Time Point Ref EGTPTREF (String): Time Point Reference pharmaversesdtm.eg_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.ex ex - Exposure SDTM (pharmaverse), from pharmaversesdtm (). 591 rows x 17 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier EXSEQ (Float64): Sequence Number EXTRT (String): Name of Actual Treatment EXDOSE (Float64): Dose per Administration EXDOSU (String): Dose Units EXDOSFRM (String): Dose Form EXDOSFRQ (String): Dosing Frequency per Interval EXROUTE (String): Route of Administration VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EXSTDTC (String): Start Date/Time of Treatment EXENDTC (String): End Date/Time of Treatment EXSTDY (Float64): Study Day of Start of Treatment EXENDY (Float64): Study Day of End of Treatment pharmaversesdtm.ex_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.ex_ophtha ex_ophtha - Exposure for Ophthalmology SDTM (pharmaverse), from pharmaversesdtm (). 591 rows x 19 columns. Variables --------- USUBJID (String): Unique Subject Identifier STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation EXSEQ (Float64): Sequence Number EXTRT (String): Name of Actual Treatment EXDOSE (Float64): Dose per Administration EXDOSU (String): Dose Units EXDOSFRM (String): Dose Form EXDOSFRQ (String): Dose Frequency per Interval EXROUTE (String): Route of Administration EXLOC (String): Location of Dose Administration EXLAT (String): Laterality VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EXSTDTC (String): Start Date/Time of Treatment EXENDTC (String): End Date/Time of Treatment EXSTDY (Float64): Study Day of Start of Treatment EXENDY (Float64): Study Day of End of Treatment pharmaversesdtm.ex_ophtha_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.ex_vaccine ex_vaccine - Exposures for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 4 rows x 19 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier EXSEQ (Float64): Sequence Number EXLNKGRP (String): Link Group ID EXLNKID (String): Link ID EXTRT (String): Name of Actual Treatment EXCAT (String): Category of Treatment EXDOSE (Float64): Dose per Administration EXDOSU (String): Dose Units EXDOSFRM (String): Dose Form EXROUTE (String): Route of Administration EXLOC (String): Location of Dose Administration EXLAT (String): Laterality VISITNUM (Float64): Visit Number VISIT (String): Visit Name EPOCH (String): Epoch EXSTDTC (String): Start Date/Time of Treatment EXENDTC (String): End Date/Time of Treatment pharmaversesdtm.ex_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.face_vaccine face_vaccine - Findings About Clinical Events for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 307 rows x 30 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier FASEQ (Int32): Sequence Number FALNKGRP (String): Link Group ID FALAT (String): Laterality FALNKID (String): Link ID FALOC (String): Location of the Finding About FATESTCD (String): Findings About Test Short Name FATEST (String): Findings About Test Name FAOBJ (String): Object of the Observation FACAT (String): Category for Findings About FASCAT (String): Subcategory for Findings About FAEVAL (String): Evaluator FAORRES (String): Result or Finding in Original Units FAORRESU (String): Original Units EPOCH (String): Epoch FADTC (String): Date/Time of Collection FADY (Float64): Study Day of Collection FATPT (String): Planned Time Point Name FATPTNUM (Float64): Planned Time Point Number FATPTREF (String): Time Point Reference FARFTDTC (String): Date/Time of Reference Time Point FAEVLINT (String): Evaluation Interval FAEVINTX (String): Evaluation Interval Text FASTAT (String): Completion Status FAREASND (String): Reason Not Performed FASTRESC (String): Character Result/Finding in Std Format FASTRESN (Float64): Numeric Result/Finding in Standard Units FASTRESU (String): Standard Units pharmaversesdtm.face_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.is_ada is_ada - Immunogenicity Specimen Assessments for ADA SDTM (pharmaverse), from pharmaversesdtm (). 691 rows x 27 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier ISSEQ (Int32): Sequence Number ISTESTCD (String): Immunogenicity Test/Exam Short Name ISTEST (String): Immunogenicity Test or Examination Name ISBDAGNT (String): Binding Agent ISCAT (String): Category for Immunogenicity Test ISORRES (String): Results or Findings in Original Units ISORRESU (String): Original Units ISSTRESC (String): Character Result/Finding in Std Format ISSTRESN (Float64): Numeric Results/Findings in Std. Units ISSTRESU (String): Standard Units ISSTAT (String): Completion Status ISREASND (String): Reason Not Done ISNAM (String): Vendor Name ISSPEC (String): Specimen Type ISBLFL (String): Baseline Flag ISLLOQ (String): Lower Limit of Quantitation VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch ISDTC (String): Date/Time of Collection ISDY (Float64): Study Day of Visit/Collection/Exam ISTPT (String): Planned Time Point Name ISTPTNUM (Float64): Planned Time Point Number pharmaversesdtm.is_ada_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.is_vaccine is_vaccine - Immunogenicity Specimen Assessments for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 16 rows x 24 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier ISSEQ (Int32): Sequence Number ISTESTCD (String): Immunogenicity Test/Exam Short Name ISTEST (String): Immunogenicity Test or Exam Name ISCAT (String): Category for Immunogenicity Test ISORRES (String): Result or Finding in Original Units ISORRESU (String): Original Units ISSTRESC (String): Character Result/Finding in Std Format ISSTRESN (Float64): Numeric Result/Finding in Standard Units ISSTRESU (String): Standard Units ISSTAT (String): Completion Status ISREASND (String): Reason Not Done ISNAM (String): Vendor Name ISSPEC (String): Specimen Type ISMETHOD (String): Method of Test or Examination ISBLFL (String): Baseline Flag ISLLOQ (Float64): Lower Limit of Quantitation VISITNUM (Float64): Visit Number EPOCH (String): Epoch ISDTC (String): Date/Time of Collection ISDY (String): Study Day of Collection ISULOQ (Float64): Upper Limit of Quantitation pharmaversesdtm.is_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.lb lb - Laboratory Measurements SDTM (pharmaverse), from pharmaversesdtm (). 59580 rows x 23 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier LBSEQ (Float64): Sequence Number LBTESTCD (String): Lab Test or Examination Short Name LBTEST (String): Lab Test or Examination Name LBCAT (String): Category for Lab Test LBORRES (String): Result or Finding in Original Units LBORRESU (String): Original Units LBORNRLO (String): Reference Range Lower Limit in Orig Unit LBORNRHI (String): Reference Range Upper Limit in Orig Unit LBSTRESC (String): Character Result/Finding in Std Format LBSTRESN (Float64): Numeric Result/Finding in Standard Units LBSTRESU (String): Standard Units LBSTNRLO (Float64): Reference Range Lower Limit-Std Units LBSTNRHI (Float64): Reference Range Upper Limit-Std Units LBNRIND (String): Reference Range Indicator LBBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit LBDTC (String): Date/Time of Specimen Collection LBDY (Float64): Study Day of Specimen Collection pharmaversesdtm.lb_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.lb_metabolic lb_metabolic - Laboratory Measurements Dataset-metabolic SDTM (pharmaverse), from pharmaversesdtm (). 309 rows x 24 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier LBSEQ (Int32): Sequence Number LBTESTCD (String): Lab Test or Examination Short Name LBTEST (String): Lab Test or Examination Name LBCAT (String): Category for Lab Test LBORRES (String): Result or Finding in Original Units LBORRESU (String): Original Units LBORNRLO (String): Reference Range Lower Limit in Orig Unit LBORNRHI (String): Reference Range Upper Limit in Orig Unit LBSTRESC (String): Character Result/Finding in Std Format LBSTRESN (Float64): Numeric Result/Finding in Standard Units LBSTRESU (String): Standard Units LBSTNRLO (Float64): Reference Range Lower Limit-Std Units LBSTNRHI (Float64): Reference Range Upper Limit-Std Units LBNRIND (String): Reference Range Indicator LBBLFL (String): Baseline Flag LBFAST (String): Fasting Status VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit LBDTC (String): Date/Time of Specimen Collection LBDY (Float64): Study Day of Specimen Collection pharmaversesdtm.lb_metabolic_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.lb_neuro lb_neuro - Laboratory Test Dataset-neuro SDTM (pharmaverse), from pharmaversesdtm (). 151 rows x 23 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier LBSEQ (Int32): Sequence Number LBTESTCD (String): Lab Test or Examination Short Name LBTEST (String): Lab Test or Examination Name LBCAT (String): Category for Lab Test LBORRES (String): Result or Finding in Original Units LBORRESU (String): Original Units LBORNRLO (String): Reference Range Lower Limit in Orig Unit LBORNRHI (String): Reference Range Upper Limit in Orig Unit LBSTRESC (String): Character Result/Finding in Std Format LBSTRESN (Float64): Numeric Result/Finding in Standard Units LBSTRESU (String): Standard Units LBSTNRLO (Float64): Reference Range Lower Limit-Std Units LBSTNRHI (Float64): Reference Range Upper Limit-Std Units LBNRIND (String): Reference Range Indicator LBBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit LBDTC (String): Date/Time of Specimen Collection LBDY (Float64): Study Day of Specimen Collection pharmaversesdtm.lb_neuro_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.lb_onco_pcwg3 lb_onco_pcwg3 - Laboratory Measurements (PSA) for Oncology SDTM (pharmaverse), from pharmaversesdtm (). 41 rows x 18 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier LBSEQ (Int32): Sequence Number LBTESTCD (String): Lab Test or Examination Short Name LBTEST (String): Lab Test or Examination Name LBCAT (String): Category for Lab Test LBORRES (String): Result or Finding in Original Units LBORRESU (String): Original Units LBSTRESC (String): Character Result/Finding in Std Format LBSTRESN (Float64): Numeric Result/Finding in Standard Units LBSTRESU (String): Standard Units LBBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit LBDTC (String): Date/Time of Specimen Collection LBDY (Float64): Study Day of Specimen Collection pharmaversesdtm.lb_onco_pcwg3_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.mb mb - Microbiology Specimen SDTM (pharmaverse), from pharmaversesdtm (). 18 rows x 21 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier MBSEQ (Int32): Sequence Number MBGRPID (Float64): Group ID MBREFID (String): Reference ID MBLNKGRP (String): Link Group ID MBTESTCD (String): Microbiology Test or Finding Short Name MBTEST (String): Microbiology Test or Finding Name MBTSTDTL (String): Measurement, Test or Examination Detail MBORRES (String): Result or Finding in Original Units MBORRESU (String): Original Units MBRSLSCL (String): Result Scale MBSTRESC (String): Result or Finding in Standard Format MBSTRESN (String): Numeric Result/Finding in Standard Units MBSTRESU (String): Standard Units MBSPEC (String): Specimen Material Type MBLOC (String): Specimen Collection Location MBMETHOD (String): Method of Test or Examination VISITNUM (Float64): Visit Number MBDTC (String): Date/Time of Collection pharmaversesdtm.mb_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.mh mh - Medical History SDTM (pharmaverse), from pharmaversesdtm (). 1818 rows x 28 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier MHSEQ (Float64): Sequence Number MHSPID (String): Sponsor-Defined Identifier MHTERM (String): Reported Term for the Medical History MHLLT (String): Lowest Level Term MHDECOD (String): Dictionary-Derived Term MHHLT (String): High Level Term MHHLGT (String): High Level Group Term MHCAT (String): Category for Medical History MHBODSYS (String): Body System or Organ Class MHSEV (String): Severity/Intensity VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit MHDTC (String): Date/Time of History Collection MHSTDTC (String): Start Date/Time of Medical History Event MHDY (Float64): Study Day of History Collection MHENDTC (String): End Date/Time of Medical History Event MHPRESP (String): Medical History Event Pre-Specified MHOCCUR (String): Medical History Occurrence MHSTRTPT (String): Start Relative to Reference Time Point MHENRTPT (String): End Relative to Reference Time Point MHSTTPT (String): Start Reference Time Point MHENTPT (String): End Reference Time Point MHENRF (String): End Relative to Reference Period MHSTAT (String): Completion Status pharmaversesdtm.mh_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.ms ms - Microbiology Susceptibility SDTM (pharmaverse), from pharmaversesdtm (). 47 rows x 23 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier MSSEQ (Int32): Sequence Number MSREFID (String): Reference ID NHOID (String): Non-host Organism ID MSGRPID (Float64): Group ID MSLNKID (String): Link ID MSTESTCD (String): Short Name of Assessment MSTEST (String): Name of Assessment MSAGENT (String): Agent Name MSCONC (String): Agent Concentration MSCONCU (String): Agent Concentration Units MSORRES (String): Result or Finding in Original Units MSORRESU (String): Original Units MSSTRESC (String): Result or Finding in Standard Format MSSTRESN (String): Numeric Result/Finding in Standard Units MSSTRESU (String): Standard Units MSSPEC (String): Specimen Material Type MSLOC (String): Location Used for the Measurement MSMETHOD (String): Method of Test or Examination VISITNUM (Float64): Visit Number MSDTC (String): Date/Time of Collection pharmaversesdtm.ms_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.nv_neuro nv_neuro - Neurological Assessment Dataset-neuro SDTM (pharmaverse), from pharmaversesdtm (). 98 rows x 21 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier NVSEQ (Int32): Sequence Number NVLNKID (Float64): Link ID NVTESTCD (String): Short Name of Nervous System Test NVTEST (String): Name of Nervous System Test NVCAT (String): Category for Nervous System Test NVLOC (String): Location Used for the Measurement NVMETHOD (String): Method of Test or Examination NVNAM (String): Vendor Name NVORRES (String): Result or Finding in Original Units NVORRESU (String): Original Units NVSTRESC (String): Character Result/Finding in Std Format NVSTRESN (Float64): Numeric Result/Finding in Standard Units NVSTRESU (String): Standard Units VISITNUM (Float64): Visit Number VISIT (String): Visit Name NVDTC (String): Date/Time of Collection NVDY (Float64): Study Day of Collection NVLOBXFL (String): Last Observation Before Exposure Flag pharmaversesdtm.nv_neuro_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.oe_ophtha oe_ophtha - Ophthalmic Examinations for Ophthalmology SDTM (pharmaverse), from pharmaversesdtm (). 26852 rows x 25 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier OESEQ (Int32): Sequence Number OECAT (String): Category for Ophthalmic Test or Exam OESCAT (String): Subcategory for Ophthalmic Test or Exam OEDTC (String): Date/Time of Collection VISIT (String): Visit Name VISITNUM (Float64): Visit Number VISITDY (Float64): Planned Study Day of Visit OESTRESN (Float64): Numeric Result/Finding in Standard Units OESTRESC (String): Character Result/Finding in Std Format OEORRES (String): Result or Finding in Original Units OETEST (String): Name of Ophthalmic Test or Examination OETESTCD (String): Short Name of Ophthalmic Test or Exam OETSTDTL (String): Ophthalmic Test or Exam Detail OELAT (String): Laterality OELOC (String): Location Used for the Measurement OEDY (Float64): Study Day of Visit/Collection/Exam OEMETHOD (String): Method of Test or Examination OEORRESU (String): Original Units OESTRESU (String): Standard Units OESTAT (String): Completion Status OETPT (String): Planned Time Point Name OETPTNUM (Float64): Planned Time Point Number pharmaversesdtm.oe_ophtha_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.pc pc - Pharmacokinetic Concentrations SDTM (pharmaverse), from pharmaversesdtm (). 4572 rows x 21 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier PCSEQ (Int32): Sequence Number PCTESTCD (String): Pharmacokinetic Test Short Name PCTEST (String): Pharmacokinetic Test Name PCORRES (String): Result or Finding in Original Units PCORRESU (String): Original Units PCSTRESC (String): Character Result/Finding in Std Format PCSTRESN (Float64): Numeric Result/Finding in Standard Units PCSTRESU (String): Standard Units PCNAM (String): Vendor Name PCSPEC (String): Specimen Material Type PCLLOQ (Float64): Lower Limit of Quantitation VISIT (String): Visit Name VISITNUM (Float64): Visit Number VISITDY (Float64): Planned Study Day of Visit PCDTC (String): Date/Time of Specimen Collection PCDY (Float64): Actual Study Day of Specimen Collection PCTPT (String): Planned Time Point Name PCTPTNUM (Float64): Planned Time Point Number pharmaversesdtm.pc_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.pp pp - Pharmacokinetic Parameters SDTM (pharmaverse), from pharmaversesdtm (). 2688 rows x 14 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier PPSEQ (Int32): Sequence Number PPTESTCD (String): Parameter Short Name PPTEST (String): Parameter Name PPCAT (String): Parameter Category PPORRES (Float64): Result or Finding in Original Units PPORRESU (String): Original Units PPSTRESC (Float64): Character Result/Finding in Std Format PPSTRESN (Float64): Numeric Result/Finding in Standard Units PPSTRESU (String): Standard Units PPSPEC (String): Specimen Material Type PPRFDTC (String): Date/Time of Reference Point pharmaversesdtm.pp_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.qs_metabolic qs_metabolic - Questionnaire Dataset-metabolic SDTM (pharmaverse), from pharmaversesdtm (). 966 rows x 18 columns. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier DOMAIN (String): Domain Abbreviation VISIT (String): Visit Name VISITNUM (Float64): Visit Number VISITDY (Float64): Planned Study Day of Visit QSBLFL (String): Baseline Flag QSDTC (String): Date/Time of Finding QSDY (Float64): Study Day of Finding QSCAT (String): Category for Questionnaire QSTEST (String): Questionnaire Test Name QSTESTCD (String): Questionnaire Test Short Name QSORRES (String): Result or Finding in Original Units QSORRESU (String): Original Units QSSTRESC (String): Character Result/Finding in Std Format QSSTRESN (Float64): Numeric Result/Finding in Standard Units QSSTRESU (String): Standard Units QSSEQ (Int32): Sequence Number pharmaversesdtm.qs_metabolic_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.qs_ophtha qs_ophtha - Questionnaire for Ophthalmology SDTM (pharmaverse), from pharmaversesdtm (). 348 rows x 20 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier QSSEQ (Int32): Sequence Number QSTESTCD (String): Question Short Name QSTEST (String): Question Name QSCAT (String): Category of Question QSSCAT (String): Subcategory for Question QSORRES (String): Finding in Original Units QSORRESU (String): Original Units QSSTRESC (String): Character Result/Finding in Std Format QSSTRESN (Float64): Numeric Finding in Standard Units QSSTRESU (String): Standard Units QSBLFL (String): Baseline Flag QSDRVFL (String): Derived Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit QSDTC (String): Date/Time of Finding QSDY (Float64): Study Day of Finding pharmaversesdtm.qs_ophtha_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.rs_onco rs_onco - Disease Response for Oncology SDTM (pharmaverse), from pharmaversesdtm (). 5808 rows x 19 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier RSSEQ (Int32): Sequence Number RSLNKGRP (String): Link Group RSTESTCD (String): Response Assessment Short Name RSTEST (String): Response Assessment Name RSCAT (String): Category for Response Assessment RSORRES (String): Response Assessment Original Result RSSTRESC (String): Response Assessment Result in Std Format RSSTAT (String): Completion Status RSREASND (String): Reason Response Assessment Not Performed RSEVAL (String): Evaluator RSEVALID (String): Evaluator Identifier RSACPTFL (String): Accepted Record Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name RSDTC (String): Date/Time of Response Assessment RSDY (Float64): Study Day of Response Assessment pharmaversesdtm.rs_onco_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.rs_onco_ca125 rs_onco_ca125 - Disease Response (GCIG) SDTM (pharmaverse), from pharmaversesdtm (). 66 rows x 13 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier RSSEQ (Int32): Sequence Number RSTESTCD (String): Assessment Short Name RSTEST (String): Assessment Name RSCAT (String): Category for Assessment RSORRES (String): Result or Finding in Original Units RSSTRESC (String): Character Result/Finding in Std Format RSEVAL (String): Evaluator VISITNUM (Int32): Visit Number VISIT (String): Visit Name RSDTC (String): Date/Time of Assessment pharmaversesdtm.rs_onco_ca125_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.rs_onco_imwg rs_onco_imwg - Disease Response (IMWG) SDTM (pharmaverse), from pharmaversesdtm (). 65 rows x 17 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier RSSEQ (Int32): Sequence Number RSLNKGRP (String): Link Group ID RSTESTCD (String): Assessment Short Name RSTEST (String): Assessment Name RSCAT (String): Category for Assessment RSORRES (String): Result or Finding in Original Units RSSTRESC (String): Character Result/Finding in Std Format RSSTAT (Boolean): Completion Status RSREASND (Boolean): Reason Not Done RSEVAL (String): Evaluator VISITNUM (Float64): Visit Number VISIT (String): Visit Name RSDTC (String): Date/Time of Assessment RSDY (Int32): Study Day of Assessment pharmaversesdtm.rs_onco_imwg_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.rs_onco_irecist rs_onco_irecist - Disease Response (iRECIST) for Oncology SDTM (pharmaverse), from pharmaversesdtm (). 376 rows x 19 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier RSSEQ (Int32): Sequence Number RSLNKGRP (String): Link Group ID RSTESTCD (String): Assessment Short Name RSTEST (String): Assessment Name RSCAT (String): Category for Assessment RSORRES (String): Result or Finding in Original Units RSSTRESC (String): Character Result/Finding in Std Format RSSTAT (String): Completion Status RSREASND (String): Reason Not Done RSEVAL (String): Evaluator RSEVALID (String): Evaluator Identifier RSACPTFL (String): Accepted Record Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name RSDTC (String): Date/Time of Assessment RSDY (Int32): Study Day of Assessment pharmaversesdtm.rs_onco_irecist_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.rs_onco_lymphoma rs_onco_lymphoma - Disease Response (Lymphoma Lugano 2014) SDTM (pharmaverse), from pharmaversesdtm (). 68 rows x 17 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier RSSEQ (Int32): Sequence Number RSTESTCD (String): Response Assessment Short Name RSTEST (String): Response Assessment Name RSCAT (String): Category for Response Assessment RSMETHOD (String): undocumented field RSSCAT (String): undocumented field RSORRES (String): Response Assessment Original Result RSSTRESC (String): Response Assessment Result in Std Format RSSTAT (String): Completion Status RSEVAL (String): Evaluator VISITNUM (Float64): Visit Number VISIT (String): Visit Name RSDTC (String): Date/Time of Response Assessment RSDY (Float64): Study Day of Response Assessment pharmaversesdtm.rs_onco_lymphoma_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.rs_onco_pcwg3 rs_onco_pcwg3 - Disease Response (PCWG3) for Oncology SDTM (pharmaverse), from pharmaversesdtm (). 90 rows x 14 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier RSSEQ (Int32): Sequence Number RSTESTCD (String): Response Assessment Short Name RSTEST (String): Response Assessment Name RSCAT (String): Category for Response Assessment RSORRES (String): Response Assessment Original Result RSSTRESC (String): Response Assessment Result in Std Format RSEVAL (String): Evaluator VISITNUM (Float64): Visit Number VISIT (String): Visit Name RSDTC (String): Date/Time of Response Assessment RSDY (Float64): Study Day of Response Assessment pharmaversesdtm.rs_onco_pcwg3_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.rs_onco_recist rs_onco_recist - Disease Response (RECIST 1.1) for Oncology SDTM (pharmaverse), from pharmaversesdtm (). 66 rows x 14 columns. Variables --------- DOMAIN (String): Domain Abbreviation STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier VISITNUM (Float64): Visit Number VISIT (String): Visit Name RSTESTCD (String): Assessment Short Name RSTEST (String): Assessment Name RSORRES (String): Result or Finding in Original Units RSSTRESC (String): Character Result/Finding in Std Format RSEVAL (String): Evaluator RSEVALID (String): Evaluator Identifier RSACPTFL (String): Accepted Record Flag RSDTC (String): Date/Time of Assessment RSSEQ (Int32): Sequence Number pharmaversesdtm.rs_onco_recist_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.sc_ophtha sc_ophtha - Subject Characteristic for Ophthalmology SDTM (pharmaverse), from pharmaversesdtm (). 254 rows x 12 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier SCSEQ (Int32): Sequence Number SCTESTCD (String): Subject Characteristic Short Name SCTEST (String): Subject Characteristic SCCAT (String): Category for Subject Characteristic SCORRES (String): Result or Finding in Original Units SCSTRESC (String): Character Result/Finding in Std Format EPOCH (String): Epoch SCDTC (String): Date/Time of Collection SCDY (Float64): Study Day of Examination pharmaversesdtm.sc_ophtha_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.sdg_db sdg_db - SDG SDTM (pharmaverse), from pharmaversesdtm (). 16 rows x 5 columns. Variables --------- termchar (String): Reported Term sdg_name (String): Name sdg_id (Int32): Name ID termvar (String): Variable version (String): Version pharmaversesdtm.sdg_db_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.smq_db smq_db - Standardized MedDRA Queries SDTM (pharmaverse), from pharmaversesdtm (). 44 rows x 6 columns. Variables --------- termchar (String): Reported Term scope (String): Scope smq_name (String): Name smq_id (Int32): Name ID version (String): Version termvar (String): Variable pharmaversesdtm.smq_db_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.suppae suppae - Supplemental Adverse Events SDTM (pharmaverse), from pharmaversesdtm (). 1191 rows x 10 columns. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin QEVAL (String): Evaluator pharmaversesdtm.suppae_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.suppce_vaccine suppce_vaccine - Supplemental Qualifiers for Clinical Events for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 4 rows x 9 columns. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier RDOMAIN (String): Related Domain Abbreviation IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QVAL (String): Data Value QLABEL (String): Qualifier Variable Label QORIG (String): Origin pharmaversesdtm.suppce_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.suppdm suppdm - Supplemental Demography SDTM (pharmaverse), from pharmaversesdtm (). 1197 rows x 10 columns. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin QEVAL (String): Evaluator pharmaversesdtm.suppdm_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.suppdm_vaccine suppdm_vaccine - Supplemental Qualifiers for Demographics for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 2 rows x 9 columns. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier RDOMAIN (String): Related Domain Abbreviation IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QVAL (String): Data Value QLABEL (String): Qualifier Variable Label QORIG (String): Origin pharmaversesdtm.suppdm_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.suppds suppds - Supplemental Disposition SDTM (pharmaverse), from pharmaversesdtm (). 3 rows x 9 columns. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin pharmaversesdtm.suppds_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.suppex_vaccine suppex_vaccine - Supplemental Qualifiers for Exposures for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 4 rows x 9 columns. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier RDOMAIN (String): Related Domain Abbreviation IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QVAL (String): Data Value QLABEL (String): Qualifier Variable Label QORIG (String): Origin pharmaversesdtm.suppex_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.suppface_vaccine suppface_vaccine - Supplemental Qualifiers for Findings About for Clinical Events for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 4 rows x 9 columns. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier RDOMAIN (String): Related Domain Abbreviation IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QVAL (String): Data Value QLABEL (String): Qualifier Variable Label QORIG (String): Origin pharmaversesdtm.suppface_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.suppis_vaccine suppis_vaccine - Supplemental Qualifiers for Immunogenicity Specimen Assessments for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 16 rows x 10 columns. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin QEVAL (Boolean): Evaluator pharmaversesdtm.suppis_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.suppnv_neuro suppnv_neuro - Supplemental for Neurological Assessment Dataset-neuro SDTM (pharmaverse), from pharmaversesdtm (). 68 rows x 10 columns. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (Int32): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin QEVAL (String): Evaluator pharmaversesdtm.suppnv_neuro_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.supprs_onco_ca125 supprs_onco_ca125 - Supplemental Qualifiers for RS_ONCO_CA125 SDTM (pharmaverse), from pharmaversesdtm (). 49 rows x 9 columns. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin pharmaversesdtm.supprs_onco_ca125_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.supprs_onco_imwg supprs_onco_imwg - Supplemental Qualifiers for RS_ONCO_IMWG SDTM (pharmaverse), from pharmaversesdtm (). 19 rows x 9 columns. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin pharmaversesdtm.supprs_onco_imwg_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.supptr_onco supptr_onco - Supplemental Tumor Results for Oncology SDTM (pharmaverse), from pharmaversesdtm (). 55995 rows x 9 columns. Variables --------- STUDYID (String): Study Identifier RDOMAIN (String): Related Domain Abbreviation USUBJID (String): Unique Subject Identifier IDVAR (String): Identifying Variable IDVARVAL (String): Identifying Variable Value QNAM (String): Qualifier Variable Name QLABEL (String): Qualifier Variable Label QVAL (String): Data Value QORIG (String): Origin pharmaversesdtm.supptr_onco_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.sv sv - Subject Visits SDTM (pharmaverse), from pharmaversesdtm (). 3559 rows x 8 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit SVSTDTC (String): Start Date/Time of Visit SVENDTC (String): End Date/Time of Visit pharmaversesdtm.sv_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.tr_onco tr_onco - Tumor Results for Oncology SDTM (pharmaverse), from pharmaversesdtm (). 55995 rows x 24 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier TRSEQ (Int32): Sequence Number TRGRPID (String): Group ID TRLNKGRP (String): Link Group TRLNKID (String): Link ID TRTESTCD (String): Tumor Assessment Short Name TRTEST (String): Tumor Assessment Test Name TRORRES (String): Result or Finding in Original Units TRORRESU (String): Original Units TRSTRESC (String): Character Result/Finding in Std Format TRSTRESN (Float64): Numeric Result/Finding in Standard Units TRSTRESU (String): Standard Units TRSTAT (String): Completion Status TRREASND (String): Reason Tumor Measurement Not Performed TRMETHOD (String): Method used to Identify the Tumor TREVAL (String): Evaluator TREVALID (String): Evaluator Identifier TRACPTFL (String): Accepted Record Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name TRDTC (String): Date/Time of Tumor Measurement TRDY (Float64): Study Day of Tumor Measurement pharmaversesdtm.tr_onco_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.tr_onco_recist tr_onco_recist - Tumor Results (RECIST 1.1) for Oncology SDTM (pharmaverse), from pharmaversesdtm (). 546 rows x 19 columns. Variables --------- DOMAIN (String): Domain Abbreviation STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier TRGRPID (String): Group ID TRLNKID (String): Link ID TRTESTCD (String): Tumor/Lesion Assessment Short Name TRTEST (String): Tumor/Lesion Assessment Test Name TRORRES (String): Result or Finding in Original Units TRORRESU (String): Original Units TRSTRESC (String): Character Result/Finding in Std Format TRSTRESN (Float64): Numeric Result/Finding in Standard Units TRSTRESU (String): Standard Units VISITNUM (Float64): Visit Number VISIT (String): Visit Name TREVAL (String): Evaluator TREVALID (String): Evaluator Identifier TRACPTFL (String): Accepted Record Flag TRDTC (String): Date/Time of Tumor/Lesion Measurement TRSEQ (Int32): Sequence Number pharmaversesdtm.tr_onco_recist_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.ts ts - Trial Design SDTM (pharmaverse), from pharmaversesdtm (). 33 rows x 6 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation TSSEQ (Float64): Sequence Number TSPARMCD (String): Trial Summary Parameter Short Name TSPARM (String): Trial Summary Parameter TSVAL (String): Parameter Value pharmaversesdtm.ts_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.tu_onco tu_onco - Tumor Identification for Oncology SDTM (pharmaverse), from pharmaversesdtm (). 7734 rows x 18 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier TUSEQ (Int32): Sequence Number TULNKID (String): Link ID TUTESTCD (String): Tumor Identification Short Name TUTEST (String): Tumor Identification Test Name TUORRES (String): Tumor Identification Result TUSTRESC (String): Tumor Identification Result Std. Format TULOC (String): Location of the Tumor TUMETHOD (String): Method of Identification TUEVAL (String): Evaluator TUEVALID (String): Evaluator Identifier TUACPTFL (String): Accepted Record Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name TUDTC (String): Date/Time of Tumor Identification TUDY (Float64): Study Day of Tumor Identification pharmaversesdtm.tu_onco_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.tu_onco_recist tu_onco_recist - Tumor Identification (RECIST 1.1) for Oncology SDTM (pharmaverse), from pharmaversesdtm (). 75 rows x 16 columns. Variables --------- DOMAIN (String): Domain Abbreviation STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier VISIT (String): Visit Name VISITNUM (Float64): Visit Number TULOC (String): Location of the Tumor/Lesion TUTESTCD (String): Tumor/Lesion ID Short Name TUTEST (String): Tumor/Lesion ID Test Name TUORRES (String): Tumor/Lesion ID Result TUSTRESC (String): Tumor/Lesion ID Result Std. Format TUMETHOD (String): Method of Identification TULNKID (String): Link ID TUEVAL (String): Evaluator TUEVALID (String): Evaluator Identifier TUACPTFL (String): Accepted Record Flag TUSEQ (Int32): Sequence Number pharmaversesdtm.tu_onco_recist_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.vs vs - Vital Signs SDTM (pharmaverse), from pharmaversesdtm (). 29643 rows x 24 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier VSSEQ (Float64): Sequence Number VSTESTCD (String): Vital Signs Test Short Name VSTEST (String): Vital Signs Test Name VSPOS (String): Vital Signs Position of Subject VSORRES (String): Result or Finding in Original Units VSORRESU (String): Original Units VSSTRESC (String): Character Result/Finding in Std Format VSSTRESN (Float64): Numeric Result/Finding in Standard Units VSSTRESU (String): Standard Units VSSTAT (String): Completion Status VSLOC (String): Location of Vital Signs Measurement VSBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit VSDTC (String): Date/Time of Measurements VSDY (Float64): Study Day of Vital Signs VSTPT (String): Planned Time Point Name VSTPTNUM (Float64): Planned Time Point Number VSELTM (String): Planned Elapsed Time from Time Point Ref VSTPTREF (String): Time Point Reference pharmaversesdtm.vs_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.vs_metabolic vs_metabolic - Vital signs Dataset-metabolic SDTM (pharmaverse), from pharmaversesdtm (). 719 rows x 24 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier VSSEQ (Int32): Sequence Number VSTESTCD (String): Vital Signs Test Short Name VSTEST (String): Vital Signs Test Name VSPOS (String): Vital Signs Position of Subject VSORRES (String): Result or Finding in Original Units VSORRESU (String): Original Units VSSTRESC (String): Character Result/Finding in Std Format VSSTRESN (Float64): Numeric Result/Finding in Standard Units VSSTRESU (String): Standard Units VSSTAT (String): Completion Status VSLOC (String): Location of Vital Signs Measurement VSBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit VSDTC (String): Date/Time of Measurements VSDY (Float64): Study Day of Vital Signs VSTPT (String): Planned Time Point Name VSTPTNUM (Float64): Planned Time Point Number VSELTM (String): Planned Elapsed Time from Time Point Ref VSTPTREF (String): Time Point Reference pharmaversesdtm.vs_metabolic_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.vs_peds vs_peds - Vital signs Dataset-pediatrics SDTM (pharmaverse), from pharmaversesdtm (). 164 rows x 26 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier VSSEQ (Int32): Sequence Number VSTESTCD (String): Vital Signs Test Short Name VSTEST (String): Vital Signs Test Name VSPOS (String): Vital Signs Position of Subject VSORRES (String): Result or Finding in Original Units VSORRESU (String): Original Units VSSTRESC (String): Character Result/Finding in Std Format VSSTRESN (Float64): Numeric Result/Finding in Standard Units VSSTRESU (String): Standard Units VSSTAT (String): Completion Status VSLOC (String): Location of Vital Signs Measurement VSBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Int32): Planned Study Day of Visit VSDTC (String): Date/Time of Measurements VSDY (Int32): Study Day of Vital Signs VSTPT (String): Planned Time Point Name VSTPTNUM (Float64): Planned Time Point Number VSELTM (String): Planned Elapsed Time from Time Point Ref VSTPTREF (String): Time Point Reference VSEVAL (String): Evaluator EPOCH (String): Epoch pharmaversesdtm.vs_peds_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaversesdtm.vs_vaccine vs_vaccine - Vital Signs for Vaccine SDTM (pharmaverse), from pharmaversesdtm (). 28 rows x 23 columns. Variables --------- STUDYID (String): Study Identifier DOMAIN (String): Domain Abbreviation USUBJID (String): Unique Subject Identifier VSSEQ (Int32): Sequence Number VSLNKID (String): Link ID VSLNKGRP (String): Link Group ID VSTESTCD (String): Vital Signs Test Short Name VSTEST (String): Vital Signs Test Name VSCAT (String): Category for Vital Signs VSSCAT (String): Subcategory for Vital Signs VSORRES (String): Result or Finding in Original Units VSORRESU (String): Original Units VSSTRESC (String): Character Result/Finding in Std Format VSSTRESN (Float64): Numeric Result/Finding in Standard Units VSSTRESU (String): Standard Units VSEVAL (String): Evaluator VSLOC (Boolean): Location of Vital Signs Measurement EPOCH (String): Epoch VSDTC (String): Date/Time of Measurements VSDY (Float64): Study Day of Vital Signs VSTPT (String): Planned Time Point Name VSTPTNUM (Int32): Planned Time Point Number VSTPTREF (String): Time Point Reference pharmaversesdtm.vs_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adadas adadas - ADAS-Cog Analysis ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 12463 rows x 40 columns. Structure: one record per subject per parameter per analysis visit per analysis date. Variables --------- STUDYID (String): Study Identifier SITEID (String): Study Site Identifier SITEGR1 (String): Pooled Site Group 1 USUBJID (String): Unique Subject Identifier TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment TRTP (String): Planned Treatment TRTPN (Float64): Planned Treatment (N) AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex ITTFL (String): Intent-to-Treat Population Flag EFFFL (String): Efficacy Population Flag COMP24FL (String): Completers of Week 24 Population Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) VISIT (String): Visit Name VISITNUM (Float64): Visit Number ADY (Float64): Analysis Relative Day ADT (Date): Analysis Date PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) AVAL (Float64): Analysis Value BASE (Float64): Baseline Value CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Record Flag 01 DTYPE (String): Derivation Type AWRANGE (String): Analysis Window Valid Relative Range AWTARGET (Float64): Analysis Window Target AWTDIFF (Float64): Analysis Window Diff from Target AWLO (Float64): Analysis Window Beginning Timepoint AWHI (Float64): Analysis Window Ending Timepoint AWU (String): Analysis Window Unit QSSEQ (Float64): Sequence Number cdiscpilotadam.adadas_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adae adae - Adverse Events Analysis Dataset ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 1191 rows x 55 columns. Structure: one record per subject per adverse event. Variables --------- STUDYID (String): Study Identifier SITEID (String): Study Site Identifier USUBJID (String): Unique Subject Identifier TRTA (String): Actual Treatment TRTAN (Float64): Actual Treatment (N) AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex SAFFL (String): Safety Population Flag TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment ASTDT (Date): Analysis Start Date ASTDTF (String): Analysis Start Date Imputation Flag ASTDY (Float64): Analysis Start Relative Day AENDT (Date): Analysis End Date AENDY (Float64): Analysis End Relative Day ADURN (Float64): AE Duration (N) ADURU (String): AE Duration Units AETERM (String): Reported Term for the Adverse Event AELLT (String): Lowest Level Term AELLTCD (Float64): Lowest Level Term Code AEDECOD (String): Dictionary-Derived Term AEPTCD (Float64): Preferred Term Code AEHLT (String): High Level Term AEHLTCD (Float64): High Level Term Code AEHLGT (String): High Level Group Term AEHLGTCD (Float64): High Level Group Term Code AEBODSYS (String): Body System or Organ Class AESOC (String): Primary System Organ Class AESOCCD (Float64): Primary System Organ Class Code AESEV (String): Severity/Intensity AESER (String): Serious Event AESCAN (String): Involves Cancer AESCONG (String): Congenital Anomaly or Birth Defect AESDISAB (String): Persist or Signif Disability/Incapacity AESDTH (String): Results in Death AESHOSP (String): Requires or Prolongs Hospitalization AESLIFE (String): Is Life Threatening AESOD (String): Occurred with Overdose AEREL (String): Causality AEACN (String): Action Taken with Study Treatment AEOUT (String): Outcome of Adverse Event AESEQ (Float64): Sequence Number TRTEMFL (String): Treatment Emergent Analysis Flag AOCCFL (String): 1st Occurrence of Any AE Flag AOCCSFL (String): 1st Occurrence of SOC Flag AOCCPFL (String): 1st Occurrence of Preferred Term Flag AOCC02FL (String): 1st Occurrence 02 Flag for Serious AOCC03FL (String): 1st Occurrence 03 Flag for Serious SOC AOCC04FL (String): 1st Occurrence 04 Flag for Serious PT CQ01NAM (String): Customized Query 01 Name AOCC01FL (String): 1st Occurrence 01 Flag for CQ01 cdiscpilotadam.adae_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adcibc adcibc - CIBIC+ Analysis ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 730 rows x 36 columns. Structure: one record per subject per parameter per analysis visit per analysis date. Variables --------- STUDYID (String): Study Identifier SITEID (String): Study Site Identifier SITEGR1 (String): Pooled Site Group 1 USUBJID (String): Unique Subject Identifier TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment TRTP (String): Planned Treatment TRTPN (Float64): Planned Treatment (N) AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex ITTFL (String): Intent-to-Treat Population Flag EFFFL (String): Efficacy Population Flag COMP24FL (String): Completers of Week 24 Population Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) VISIT (String): Visit Name VISITNUM (Float64): Visit Number ADY (Float64): Analysis Relative Day ADT (Date): Analysis Date PARAMCD (String): Parameter Code PARAM (String): Parameter PARAMN (Float64): Parameter (N) AVAL (Float64): Analysis Value ANL01FL (String): Analysis Record Flag 01 DTYPE (String): Derivation Type AWRANGE (String): Analysis Window Valid Relative Range AWTARGET (Float64): Analysis Window Target AWTDIFF (Float64): Analysis Window Diff from Target AWLO (Float64): Analysis Window Beginning Timepoint AWHI (Float64): Analysis Window Ending Timepoint AWU (String): Analysis Window Unit QSSEQ (Float64): Sequence Number cdiscpilotadam.adcibc_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adlbc adlbc - Analysis Dataset Lab Blood Chemistry ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 37132 rows x 46 columns. Structure: one record per subject per parameter per analysis visit. Variables --------- STUDYID (String): Study Identifier SUBJID (String): Subject Identifier for the Study USUBJID (String): Unique Subject Identifier TRTP (String): Planned Treatment TRTPN (Float64): Planned Treatment (N) TRTA (String): Actual Treatment TRTAN (Float64): Actual Treatment (N) TRTSDT (Float64): Date of First Exposure to Treatment TRTEDT (Float64): Date of Last Exposure to Treatment AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex COMP24FL (String): Completers of Week 24 Population Flag DSRAEFL (String): Discontinued due to AE? SAFFL (String): Safety Population Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ADY (Float64): Analysis Relative Day ADT (Float64): Analysis Date VISIT (String): Visit Name VISITNUM (Float64): Visit Number PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 AVAL (Float64): Analysis Value BASE (Float64): Baseline Value CHG (Float64): Change from Baseline A1LO (Float64): Analysis Range 1 Lower Limit A1HI (Float64): Analysis Range 1 Upper Limit R2A1LO (Float64): Ratio to Analysis Range 1 Lower Limit R2A1HI (Float64): Ratio to Analysis Range 1 Upper Limit BR2A1LO (Float64): Base Ratio to Analysis Range 1 Lower Lim BR2A1HI (Float64): Base Ratio to Analysis Range 1 Upper Lim ANL01FL (String): Analysis Flag 01 ALBTRVAL (Float64): Amount Threshold Range ANRIND (String): Analysis Reference Range Indicator BNRIND (String): Baseline Reference Range Indicator ABLFL (String): Baseline Record Flag AENTMTFL (String): Last value in treatment visit LBSEQ (Float64): Sequence Number LBNRIND (String): Reference Range Indicator LBSTRESN (Float64): Numeric Result/Finding in Standard Units cdiscpilotadam.adlbc_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adlbcpv adlbcpv - Analysis Dataset Lab Blood Chemistry (Previous Visit) ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 37132 rows x 46 columns. Structure: one record per subject per parameter per analysis visit. Variables --------- STUDYID (String): Study Identifier SUBJID (String): Subject Identifier for the Study USUBJID (String): Unique Subject Identifier TRTP (String): Planned Treatment TRTPN (Float64): Planned Treatment (N) TRTA (String): Actual Treatment TRTAN (Float64): Actual Treatment (N) TRTSDT (Float64): Date of First Exposure to Treatment TRTEDT (Float64): Date of Last Exposure to Treatment AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex COMP24FL (String): Completers of Week 24 Population Flag DSRAEFL (String): Discontinued due to AE? SAFFL (String): Safety Population Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ADY (Float64): Analysis Relative Day ADT (Float64): Analysis Date VISIT (String): Visit Name VISITNUM (Float64): Visit Number PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 AVAL (Float64): Analysis Value BASE (Float64): Baseline Value CHG (Float64): Change from Baseline A1LO (Float64): Analysis Range 1 Lower Limit A1HI (Float64): Analysis Range 1 Upper Limit R2A1LO (Float64): Ratio to Analysis Range 1 Lower Limit R2A1HI (Float64): Ratio to Analysis Range 1 Upper Limit BR2A1LO (Float64): Base Ratio to Analysis Range 1 Lower Lim BR2A1HI (Float64): Base Ratio to Analysis Range 1 Upper Lim ANL01FL (String): Analysis Flag 01 ALBTRVAL (Float64): Amount Threshold Range ANRIND (String): Analysis Reference Range Indicator BNRIND (String): Baseline Reference Range Indicator ABLFL (String): Baseline Record Flag AENTMTFL (String): Last value in treatment visit LBSEQ (Float64): Sequence Number LBNRIND (String): Reference Range Indicator LBSTRESN (Float64): Numeric Result/Finding in Standard Units cdiscpilotadam.adlbcpv_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adlbh adlbh - Analysis Dataset Lab Hematology ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 24966 rows x 46 columns. Structure: one record per subject per parameter per analysis visit. Variables --------- STUDYID (String): Study Identifier SUBJID (String): Subject Identifier for the Study USUBJID (String): Unique Subject Identifier TRTP (String): Planned Treatment TRTPN (Float64): Planned Treatment (N) TRTA (String): Actual Treatment TRTAN (Float64): Actual Treatment (N) TRTSDT (Float64): Date of First Exposure to Treatment TRTEDT (Float64): Date of Last Exposure to Treatment AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex COMP24FL (String): Completers of Week 24 Population Flag DSRAEFL (String): Discontinued due to AE? SAFFL (String): Safety Population Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ADY (Float64): Analysis Relative Day ADT (Float64): Analysis Date VISIT (String): Visit Name VISITNUM (Float64): Visit Number PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 AVAL (Float64): Analysis Value BASE (Float64): Baseline Value CHG (Float64): Change from Baseline A1LO (Float64): Analysis Range 1 Lower Limit A1HI (Float64): Analysis Range 1 Upper Limit R2A1LO (Float64): Ratio to Analysis Range 1 Lower Limit R2A1HI (Float64): Ratio to Analysis Range 1 Upper Limit BR2A1LO (Float64): Base Ratio to Analysis Range 1 Lower Lim BR2A1HI (Float64): Base Ratio to Analysis Range 1 Upper Lim ANL01FL (String): Analysis Flag 01 ALBTRVAL (Float64): Amount Threshold Range ANRIND (String): Analysis Reference Range Indicator BNRIND (String): Baseline Reference Range Indicator ABLFL (String): Baseline Record Flag AENTMTFL (String): Last value in treatment visit LBSEQ (Float64): Sequence Number LBNRIND (String): Reference Range Indicator LBSTRESN (Float64): Numeric Result/Finding in Standard Units cdiscpilotadam.adlbh_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adlbhpv adlbhpv - Analysis Dataset Lab Hematology (Previous Visit) ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 24966 rows x 46 columns. Structure: one record per subject per parameter per analysis visit. Variables --------- STUDYID (String): Study Identifier SUBJID (String): Subject Identifier for the Study USUBJID (String): Unique Subject Identifier TRTP (String): Planned Treatment TRTPN (Float64): Planned Treatment (N) TRTA (String): Actual Treatment TRTAN (Float64): Actual Treatment (N) TRTSDT (Float64): Date of First Exposure to Treatment TRTEDT (Float64): Date of Last Exposure to Treatment AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex COMP24FL (String): Completers of Week 24 Population Flag DSRAEFL (String): Discontinued due to AE? SAFFL (String): Safety Population Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ADY (Float64): Analysis Relative Day ADT (Float64): Analysis Date VISIT (String): Visit Name VISITNUM (Float64): Visit Number PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 AVAL (Float64): Analysis Value BASE (Float64): Baseline Value CHG (Float64): Change from Baseline A1LO (Float64): Analysis Range 1 Lower Limit A1HI (Float64): Analysis Range 1 Upper Limit R2A1LO (Float64): Ratio to Analysis Range 1 Lower Limit R2A1HI (Float64): Ratio to Analysis Range 1 Upper Limit BR2A1LO (Float64): Base Ratio to Analysis Range 1 Lower Lim BR2A1HI (Float64): Base Ratio to Analysis Range 1 Upper Lim ANL01FL (String): Analysis Flag 01 ALBTRVAL (Float64): Amount Threshold Range ANRIND (String): Analysis Reference Range Indicator BNRIND (String): Baseline Reference Range Indicator ABLFL (String): Baseline Record Flag AENTMTFL (String): Last value in treatment visit LBSEQ (Float64): Sequence Number LBNRIND (String): Reference Range Indicator LBSTRESN (Float64): Numeric Result/Finding in Standard Units cdiscpilotadam.adlbhpv_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adlbhy adlbhy - Analysis Dataset Lab Hy's Law ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 9954 rows x 43 columns. Structure: one record per subject per parameter per analysis visit. Variables --------- STUDYID (String): Study Identifier SUBJID (String): Subject Identifier for the Study USUBJID (String): Unique Subject Identifier TRTP (String): Planned Treatment TRTPN (Float64): Planned Treatment (N) TRTA (String): Actual Treatment TRTAN (Float64): Actual Treatment (N) TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex COMP24FL (String): Completers of Week 24 Population Flag DSRAEFL (String): Discontinued due to AE? SAFFL (String): Safety Population Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ADY (Float64): Analysis Relative Day ADT (Date): Analysis Date VISIT (String): Visit Name VISITNUM (Float64): Visit Number PARAMTYP (String): Parameter Type PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 AVAL (Float64): Analysis Value BASE (Float64): Baseline Value A1LO (Float64): Analysis Range 1 Lower Limit A1HI (Float64): Analysis Range 1 Upper Limit R2A1LO (Float64): Ratio to Analysis Range 1 Lower Limit R2A1HI (Float64): Ratio to Analysis Range 1 Upper Limit BR2A1LO (Float64): Base Ratio to Analysis Range 1 Lower Lim BR2A1HI (Float64): Base Ratio to Analysis Range 1 Upper Lim ABLFL (String): Baseline Record Flag SHIFT1 (String): Shift 1 SHIFT1N (Float64): Shift 1 (N) CRIT1 (String): Analysis Criterion 1 CRIT1FL (String): Criterion 1 Evaluation Result Flag CRIT1FN (Float64): Criterion 1 Evaluation Result Flag (N) cdiscpilotadam.adlbhy_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adnpix adnpix - NPI-X Item Analysis Data ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 31140 rows x 41 columns. Structure: one record per subject per parameter per analysis visit per analysis date. Variables --------- STUDYID (String): Study Identifier SITEID (String): Study Site Identifier SITEGR1 (String): Pooled Site Group 1 USUBJID (String): Unique Subject Identifier TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment TRTP (String): Planned Treatment TRTPN (Float64): Planned Treatment (N) AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex ITTFL (String): Intent-to-Treat Population Flag EFFFL (String): Efficacy Population Flag COMP24FL (String): Completers of Week 24 Population Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ADY (Float64): Analysis Relative Day ADT (Date): Analysis Date VISITNUM (Float64): Visit Number VISIT (String): Visit Name PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARAMTYP (String): Parameter Type AVAL (Float64): Analysis Value BASE (Float64): Baseline Value CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 DTYPE (String): Derivation Type AWRANGE (String): Analysis Window Valid Relative Range AWTARGET (Float64): Analysis Window Target AWTDIFF (Float64): Analysis Window Diff from Target AWLO (Float64): Analysis Window Beginning Timepoint AWHI (Float64): Analysis Window Ending Timepoint AWU (String): Analysis Window Unit QSSEQ (Float64): Sequence Number cdiscpilotadam.adnpix_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adsl adsl - Subject-Level Analysis ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 254 rows x 49 columns. Structure: one record per subject. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier SITEGR1 (String): Pooled Site Group 1 ARM (String): Description of Planned Arm TRT01P (String): Planned Treatment for Period 01 TRT01PN (Float64): Planned Treatment for Period 01 (N) TRT01A (String): Actual Treatment for Period 01 TRT01AN (Float64): Actual Treatment for Period 01 (N) TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment TRTDURD (Float64): Total Treatment Duration (Days) AVGDD (Float64): Avg Daily Dose (as planned) CUMDOSE (Float64): Cumulative Dose (as planned) AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) AGEU (String): Age Units RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ITTFL (String): Intent-To-Treat Population Flag EFFFL (String): Efficacy Population Flag COMP8FL (String): Completers of Week 8 Population Flag COMP16FL (String): Completers of Week 16 Population Flag COMP24FL (String): Completers of Week 24 Population Flag DISCONFL (String): Did the Subject Discontinue the Study? DSRAEFL (String): Discontinued due to AE? DTHFL (String): Subject Died? BMIBL (Float64): Baseline BMI (kg/m^2) BMIBLGR1 (String): Pooled Baseline BMI Group 1 HEIGHTBL (Float64): Baseline Height (cm) WEIGHTBL (Float64): Baseline Weight (kg) EDUCLVL (Float64): Years of Education DISONSDT (Date): Date of Onset of Disease DURDIS (Float64): Duration of Disease (Months) DURDSGR1 (String): Pooled Disease Duration Group 1 VISIT1DT (Date): Date of Visit 1 RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time VISNUMEN (Float64): End of Trt Visit (Vis 12 or Early Term.) RFENDT (Date): Date of Discontinuation/Completion DCDECOD (String): Standardized Disposition Term EOSSTT (String): End of Study Status DCSREAS (String): Reason for Discontinuation from Study MMSETOT (Float64): MMSE Total cdiscpilotadam.adsl_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.adtte adtte - AE Time To 1st Derm. Event Analysis ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 254 rows x 26 columns. Structure: one record per subject per parameter. Variables --------- STUDYID (String): Study Identifier SITEID (String): Study Site Identifier USUBJID (String): Unique Subject Identifier AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment TRTDUR (Float64): Duration of treatment (days) TRTP (String): Planned Treatment TRTA (String): Actual Treatment TRTAN (Float64): Actual Treatment (N) PARAM (String): Parameter PARAMCD (String): Parameter Code AVAL (Float64): Analysis Value STARTDT (Date): Time to Event Origin Date for Subject ADT (Date): Analysis Date CNSR (Float64): Censor EVNTDESC (String): Event or Censoring Description SRCDOM (String): Source Domain SRCVAR (String): Source Variable SRCSEQ (Float64): Source Sequence Number SAFFL (String): Safety Population Flag cdiscpilotadam.adtte_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) cdiscpilotadam.advs advs - Vital Signs Analysis Dataset ADaM (CDISC pilot), from the CDISC SDTM/ADaM Pilot Project (). 32139 rows x 35 columns. Structure: one record per subject per parameter per analysis visit per analysis timepoint. Variables --------- STUDYID (String): Study Identifier SITEID (String): Study Site Identifier USUBJID (String): Unique Subject Identifier AGE (Float64): Age AGEGR1 (String): Pooled Age Group 1 AGEGR1N (Float64): Pooled Age Group 1 (N) RACE (String): Race RACEN (Float64): Race (N) SEX (String): Sex SAFFL (String): Safety Population Flag TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment TRTP (String): Planned Treatment TRTPN (Float64): Planned Treatment (N) TRTA (String): Actual Treatment TRTAN (Float64): Actual Treatment (N) PARAMCD (String): Parameter Code PARAM (String): Parameter PARAMN (Float64): Parameter (N) ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day ATPTN (Float64): Analysis Timepoint (N) ATPT (String): Analysis Timepoint AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) AVAL (Float64): Analysis Value BASE (Float64): Baseline Value BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline VISITNUM (Float64): Visit Number VISIT (String): Visit Name VSSEQ (Float64): Sequence Number ANL01FL (String): Analysis Flag 01 ABLFL (String): Baseline Record Flag cdiscpilotadam.advs_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adab adab - Anti-Drug Antibody Analysis Dataset ADaM (pharmaverse), from pharmaverseadam (). 6430 rows x 72 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 COUNTRY (String): Country ETHNIC (String): Ethnicity AGE (Float64): Age AGEU (String): Age Units SEX (String): Sex RACE (String): Race SAFFL (String): Safety Population Flag TRT01P (String): Description of Planned Arm TRT01A (String): Description of Actual Arm TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSDT (Date): Date of First Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment ISSEQ (Int32): Sequence Number ISTESTCD (String): Immunogenicity Test/Exam Short Name ISTEST (String): Immunogenicity Test or Examination Name ISCAT (String): Category for Immunogenicity Test ISBDAGNT (String): Binding Agent ISSTRESC (String): Character Result/Finding in Std Format ISSTRESN (Float64): Numeric Results/Findings in Std. Units ISSTRESU (String): Standard Units ISSTAT (String): Completion Status ISREASND (String): Reason Not Done ISSPEC (String): Specimen Type DTL (Float64): Drug Tolerance Level MRT (Float64): Minimum Reportable Titer VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EPOCH (String): Epoch ISDTC (String): Date/Time of Collection ISDY (Float64): Study Day of Visit/Collection/Exam ISTPT (String): Planned Time Point Name ISTPTNUM (Float64): Planned Time Point Number PARAM (String): Parameter PARAMCD (String): Parameter Code PARCAT1 (String): Parameter Category 1 AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) AVALU (String): Analysis Value Unit BASETYPE (String): Baseline Type BASE (Float64): Baseline Value CHG (Float64): Change from Baseline DTYPE (String): Derivation Type ADTM (Datetime): Analysis Datetime ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day ATMF (String): Analysis Time Imputation Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ATPT (String): Analysis Timepoint APHASE (String): Phase APHASEN (Int32): Phase (N) APERIOD (Float64): Period APERIODC (String): Period (C) FANLDTM (Datetime): First Datetime of Dose for Analyte FANLDT (Date): First Date of Dose for Analyte FANLTM (Time): First Time of Dose for Analyte FANLTMF (String): First Time of Dose for Analyte ImputeFL NFRLT (Float64): Nom. Rel. Time from Analyte First Dose AFRLT (Float64): Act. Rel. Time from Analyte First Dose FRLTU (String): Rel. Time from First Dose Unit ABLFL (String): Baseline Record Flag ADABLPFL (String): Baseline ADA Eval. Param-Level Flag ADPBLPFL (String): Post-Baseline ADA Eval. Param-Level Flag ADAFL (String): ADA Population Flag pharmaverseadam.adab_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adae adae - Adverse Events Analysis ADaM (pharmaverse), from pharmaverseadam (). 1191 rows x 107 columns. Structure: One record per subject per adverse event. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 AESEQ (Float64): Sequence Number AETERM (String): Reported Term for the Adverse Event AEDECOD (String): Dictionary-Derived Term AEBODSYS (String): Body System or Organ Class AEBDSYCD (Float64): Body System or Organ Class Code AELLT (String): Lowest Level Term AELLTCD (Float64): Lowest Level Term Code AEPTCD (Float64): Preferred Term Code AEHLT (String): High Level Term AEHLTCD (Float64): High Level Term Code AEHLGT (String): High Level Group Term AEHLGTCD (Float64): High Level Group Term Code AESOC (String): Primary System Organ Class AESOCCD (Float64): Primary System Organ Class Code AESTDTC (String): Start Date/Time of Adverse Event ASTDT (Date): Analysis Start Date ASTDTM (Datetime): Analysis Start Date/Time ASTDTF (String): Analysis Start Date Imputation Flag ASTTMF (String): Analysis Start Time Imputation Flag AEENDTC (String): End Date/Time of Adverse Event AENDT (Date): Analysis End Date AENDTM (Datetime): Analysis End Date/Time AENDTF (String): Analysis End Date Imputation Flag AENTMF (String): Analysis End Time Imputation Flag ASTDY (Float64): Analysis Start Relative Day AESTDY (Float64): Study Day of Start of Adverse Event AENDY (Float64): Analysis End Relative Day AEENDY (Float64): Study Day of End of Adverse Event ADURN (Float64): Analysis Duration (N) ADURU (String): Analysis Duration Units TRTEMFL (String): Treatment Emergent Analysis Flag AOCCIFL (String): 1st Max Sev./Int. Occurrence Flag AESER (String): Serious Event AESDTH (String): Results in Death AESLIFE (String): Is Life Threatening AESHOSP (String): Requires or Prolongs Hospitalization AESDISAB (String): Persist or Signif Disability/Incapacity AESCONG (String): Congenital Anomaly or Birth Defect AESEV (String): Severity/Intensity ASEV (String): Analysis Severity/Intensity ASEVN (Int32): Analysis Severity/Intensity (N) AEREL (String): Causality AREL (String): Analysis Causality AEACN (String): Action Taken with Study Treatment AESPID (String): Sponsor-Defined Identifier AEOUT (String): Outcome of Adverse Event AESCAN (String): Involves Cancer AESOD (String): Occurred with Overdose AEDTC (String): Date/Time of Collection LDOSEDTM (Datetime): End Date/Time of Last Dose DOSEON (Float64): Treatment Dose DOSEU (String): Treatment Dose Unit pharmaverseadam.adae_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adapet_neuro adapet_neuro - Amyloid PET Scan Analysis Dataset ADaM (pharmaverse), from pharmaverseadam (). 83 rows x 49 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier DOMAIN (String): Domain Abbreviation ASEQ (Int32): Analysis Sequence Number TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) PARAM (String): Parameter PARAMCD (String): Parameter Code AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) AVALU (String): Analysis Value Unit BASE (Float64): Baseline Value BASEC (String): Baseline Value (C) BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline CRIT1 (String): Analysis Criterion 1 CRIT1FL (String): Criterion 1 Evaluation Result Flag ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ANL02FL (String): Analysis Flag 02 ONTRTFL (String): On Treatment Record Flag NVSEQ (Int32): Sequence Number NVLNKID (Float64): Link ID NVTESTCD (String): Short Name of Nervous System Test NVTEST (String): Name of Nervous System Test NVCAT (String): Category for Nervous System Test NVLOC (String): Location Used for the Measurement NVNAM (String): Vendor Name NVORRES (String): Result or Finding in Original Units NVORRESU (String): Original Units NVSTRESC (String): Character Result/Finding in Std Format NVSTRESN (Float64): Numeric Result/Finding in Standard Units NVSTRESU (String): Standard Units NVMETHOD (String): Method of Test or Examination NVLOBXFL (String): Last Observation Before Exposure Flag REFREG (String): Reference Region AGTRT (String): Reported Agent Name AGCAT (String): Category for Agent VISITNUM (Float64): Visit Number VISIT (String): Visit Name NVDTC (String): Date/Time of Collection NVDY (Float64): Study Day of Visit/Collection/Exam pharmaverseadam.adapet_neuro_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adbcva_ophtha adbcva_ophtha - Best Corrected Visual Acuity Analysis ADaM (pharmaverse), from pharmaverseadam (). 7672 rows x 71 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier DOMAIN (String): Domain Abbreviation TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ATPT (String): Analysis Timepoint ATPTN (Float64): Analysis Timepoint (N) PARAM (String): Parameter PARAMCD (String): Parameter Code AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) AVALU (String): Analysis Value Unit AVALCAT1 (String): Analysis Value Category 1 AVALCA1N (Float64): Analysis Value Category 1 (N) BASE (Float64): Baseline Value BASEC (String): Baseline Value (C) BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline CRIT1 (String): Analysis Criterion 1 CRIT1FL (String): Criterion 1 Evaluation Result Flag CRIT2 (String): Analysis Criterion 2 CRIT2FL (String): Criterion 2 Evaluation Result Flag CRIT3 (String): Analysis Criterion 3 CRIT3FL (String): Criterion 3 Evaluation Result Flag CRIT4 (String): Analysis Criterion 4 CRIT4FL (String): Criterion 4 Evaluation Result Flag CRIT5 (String): Analysis Criterion 5 CRIT5FL (String): Criterion 5 Evaluation Result Flag CRIT6 (String): Analysis Criterion 6 CRIT6FL (String): Criterion 6 Evaluation Result Flag CRIT7 (String): Analysis Criterion 7 CRIT7FL (String): Criterion 7 Evaluation Result Flag CRIT8 (String): Analysis Criterion 8 CRIT8FL (String): Criterion 8 Evaluation Result Flag DTYPE (String): Derivation Type ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ANL02FL (String): Analysis Flag 02 ONTRTFL (String): On Treatment Record Flag OESEQ (Int32): Sequence Number OECAT (String): Category for Ophthalmic Test or Exam OESCAT (String): Subcategory for Ophthalmic Test or Exam OEDTC (String): Date/Time of Collection VISIT (String): Visit Name VISITNUM (Float64): Visit Number VISITDY (Float64): Planned Study Day of Visit OESTRESN (Float64): Numeric Result/Finding in Standard Units OESTRESC (String): Character Result/Finding in Std Format OEORRES (String): Result or Finding in Original Units OETEST (String): Name of Ophthalmic Test or Exam OETESTCD (String): Short Name of Ophthalmic Test or Exam OETSTDTL (String): Ophthalmic Test or Exam Detail OELAT (String): Laterality OELOC (String): Location Used for the Measurement OEDY (Float64): Study Day of Visit/Collection/Exam OEMETHOD (String): Method of Test or Examination OEORRESU (String): Original Units OESTRESU (String): Standard Units OESTAT (String): Completion Status OETPT (String): Planned Time Point Name OETPTNUM (Float64): Planned Time Point Number STUDYEYE (String): Study Eye Location AFEYE (String): Affected Eye WORS01FL (String): Worst Post Baseline Obs pharmaverseadam.adbcva_ophtha_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adce_vaccine adce_vaccine - Clinical Events Analysis for Vaccine ADaM (pharmaverse), from pharmaverseadam (). 44 rows x 56 columns. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (Float64): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation ASEQ (Int32): Analysis Sequence Number AGE (Float64): Age AGEU (String): Age Units SEX (String): Sex RACE (String): Race ETHNIC (String): Ethnicity TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment APERSDT (Date): Period Start Date APEREDT (Date): Period End Date APERSTDY (Float64): Analysis Sub-period Start Relative Day CESEQ (Float64): Sequence Number CETERM (String): Reported Term for the Clinical Event CEDECOD (String): Dictionary-Derived Term CECAT (String): Category for the Clinical Event CESCAT (String): Subcategory for the Clinical Event CESTDTC (String): Start Date/Time of Clinical Event ASTDT (Date): Analysis Start Date CEENDTC (String): End Date/Time of Clinical Event AENDT (Date): Analysis End Date ASTDY (Float64): Analysis Start Relative Day AENDY (Float64): Analysis End Relative Day ADURN (Float64): Analysis Duration (N) ADURU (String): Analysis Duration Units CEDUR (String): Duration of Clinical Event APERIOD (Int32): Period CEOCCUR (String): Clinical Event Occurrence CEPRESP (String): Clinical Event Pre-specified AOCC01FL (String): Event Occurrence Flag ASEV (String): Analysis Severity/Intensity ASEVN (Int32): Analysis Severity/Intensity (N) AREL (String): Analysis Causality CELNKID (String): Link ID CELNKGRP (String): Link Group ID CELAT (String): Laterality CELOC (String): Location of Event CESEV (String): Severity/Intensity CEREL (String): Causality CEOUT (String): Outcome of Event EPOCH (String): Epoch CEDTC (String): Date/Time of Event Collection CETPT (String): Planned Time Point Name CETPTNUM (Float64): Planned Time Point Number CETPTREF (String): Time Point Reference CERFTDTC (String): Date/Time of Reference Time Point CEEVINTX (String): Evaluation Interval Text CESTAT (String): Completion Status CEREASND (String): Reason Clinical Event Not Collected pharmaverseadam.adce_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adcm adcm - Concomitant Medications Analysis ADaM (pharmaverse), from pharmaverseadam (). 7510 rows x 95 columns. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRTP (String): Planned Treatment TRTA (String): Actual Treatment TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Treatment End Datetime Imput Flag APHASE (String): Phase APHASEN (Float64): Description of Phase N EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 CMSEQ (Float64): Sequence Number CMDECOD (String): Standardized Medication Name CMTRT (String): Reported Name of Drug, Med, or Therapy CMCLAS (String): Medication Class CMSTDTC (String): Start Date/Time of Medication ASTDT (Date): Analysis Start Date ASTDTM (Datetime): Analysis Start Date/Time ASTDTF (String): Analysis Start Date Imputation Flag ASTTMF (String): Analysis Start Time Imputation Flag CMENDTC (String): End Date/Time of Medication AENDT (Date): Analysis End Date AENDTM (Datetime): Analysis End Date/Time AENDTF (String): Analysis End Date Imputation Flag AENTMF (String): Analysis End Time Imputation Flag ASTDY (Float64): Analysis Start Relative Day CMSTDY (Float64): Study Day of Start of Medication AENDY (Float64): Analysis End Relative Day CMENDY (Float64): Study Day of End of Medication ADURN (Float64): Analysis Duration (N) ADURU (String): Analysis Duration Units ANL01FL (String): Analysis Flag 01 ONTRTFL (String): On Treatment Record Flag PREFL (String): Pre-treatment Flag FUPFL (String): Follow-up Flag AOCCPFL (String): 1st Occurrence of Preferred Term Flag CMINDC (String): Indication CMDOSE (Float64): Dose per Administration CMDOSU (String): Dose Units CMDOSFRQ (String): Dosing Frequency per Interval CMROUTE (String): Route of Administration CMSPID (String): Sponsor-Defined Identifier CMENRTPT (String): End Relative to Reference Time Point VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit CMDTC (String): Date/Time of Collection pharmaverseadam.adcm_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adcoeq_metabolic adcoeq_metabolic - Questionnaires Analysis for Metabolic ADaM (pharmaverse), from pharmaverseadam (). 1110 rows x 85 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) BASE (Float64): Baseline Value CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline ABLFL (String): Baseline Record Flag VISIT (String): Visit Name VISITNUM (Float64): Visit Number VISITDY (Float64): Planned Study Day of Visit QSBLFL (String): Baseline Flag QSDTC (String): Date/Time of Finding QSDY (Float64): Study Day of Finding QSCAT (String): Category for Questionnaire QSTEST (String): Questionnaire Test Name QSTESTCD (String): Questionnaire Test Short Name QSORRES (String): Result or Finding in Original Units QSORRESU (String): Original Units QSSTRESC (String): Character Result/Finding in Std Format QSSTRESN (Float64): Numeric Result/Finding in Standard Units QSSTRESU (String): Standard Units QSSEQ (Int32): Sequence Number pharmaverseadam.adcoeq_metabolic_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adeg adeg - Electrocardiogram Tests Analysis ADaM (pharmaverse), from pharmaverseadam (). 78756 rows x 108 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRTP (String): Planned Treatment TRTA (String): Actual Treatment TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 ADT (Date): Analysis Date ADTM (Datetime): Analysis Datetime ADY (Float64): Analysis Relative Day ATMF (String): Analysis Time Imputation Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ATPT (String): Analysis Timepoint ATPTN (Float64): Analysis Timepoint (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) AVALCAT1 (String): Analysis Value Category 1 AVALCA1N (Float64): Analysis Value Category 1 (N) BASE (Float64): Baseline Value BASEC (String): Baseline Value (C) BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline CHGCAT1 (String): Change from Baseline Category 1 CHGCAT1N (Float64): Change from Baseline Category 1 (N) PCHG (Float64): Percent Change from Baseline DTYPE (String): Derivation Type ANRIND (String): Analysis Reference Range Indicator BNRIND (String): Baseline Reference Range Indicator ANRLO (Float64): Analysis Normal Range Lower Limit ANRHI (Float64): Analysis Normal Range Upper Limit ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ONTRTFL (String): On Treatment Record Flag EGSEQ (Float64): Sequence Number EGTESTCD (String): ECG Test or Examination Short Name EGTEST (String): ECG Test or Examination Name EGORRES (String): Result or Finding in Original Units EGORRESU (String): Original Units EGSTRESC (String): Character Result/Finding in Std Format EGSTRESN (Float64): Numeric Result/Finding in Standard Units EGSTRESU (String): Standard Units EGSTAT (String): Completion Status EGLOC (String): Lead Location Used for Measurement EGBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EGDTC (String): Date/Time of ECG EGDY (Float64): Study Day of ECG EGTPT (String): Planned Time Point Name EGTPTNUM (Float64): Planned Time Point Number EGELTM (String): Planned Elapsed Time from Time Point Ref EGTPTREF (String): Time Point Reference pharmaverseadam.adeg_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adex adex - Exposure Analysis ADaM (pharmaverse), from pharmaverseadam (). 6315 rows x 92 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 EXTRT (String): Name of Treatment EXDOSE (Float64): Dose EXDOSFRM (String): Dose Form EXDOSFRQ (String): Dosing Frequency per Interval EXROUTE (String): Route of Administration EXADJ (String): Reason for Dose Adjustment EXSTDTC (String): Start Date/Time of Treatment EXENDTC (String): End Date/Time of Treatment EXSTDY (Float64): Study Day of Start of Treatment EXENDY (Float64): Study Day of End of Treatment EXSEQ (Float64): Sequence Number ASTDT (Date): Analysis Start Date AENDT (Date): Analysis End Date EXDURD (Float64): Duration of Treatment (Days) EXDOSU (String): Dose Units VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit EXPLDOS (Float64): Planned Dose ASTDTM (Datetime): Analysis Start Datetime ASTDTF (String): Analysis Start Date Imputation Flag ASTTMF (String): Analysis Start Time Imputation Flag AENDTM (Datetime): Analysis End Datetime AENDTF (String): Analysis End Date Imputation Flag AENTMF (String): Analysis End Time Imputation Flag ASTDY (Float64): Analysis Start Relative Day AENDY (Float64): Analysis End Relative Day DOSEO (Float64): Dose O PDOSEO (Float64): PDose O PARAMCD (String): Parameter Code AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) PARCAT1 (String): Parameter Category 1 PARAM (String): Parameter PARAMN (Float64): Parameter (N) AVALCAT1 (String): Analysis Value Category 1 pharmaverseadam.adex_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adface_vaccine adface_vaccine - Findings About Clinical Events Analysis ADaM (pharmaverse), from pharmaverseadam (). 371 rows x 61 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (Float64): Study Site Identifier AGE (Float64): Age AGEU (String): Age Units SEX (String): Sex RACE (String): Race SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRTP (String): Planned Treatment TRTA (String): Actual Treatment TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRT02P (String): Planned Treatment for Period 02 TRT02A (String): Actual Treatment for Period 02 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment APERSDT (Date): Period Start Date APEREDT (Date): Period End Date ADT (Date): Analysis Date ADTM (Datetime): Analysis Datetime ADY (Float64): Analysis Relative Day ATPT (String): Analysis Timepoint ATPTN (Float64): Analysis Timepoint (N) ATPTREF (String): Analysis Timepoint Reference APERIOD (Int32): Period PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 PARCAT2 (String): Parameter Category 2 AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) ANL01FL (String): Analysis Flag 01 ANL02FL (String): Analysis Flag 02 ANL03FL (String): Analysis Flag 03 FATEST (String): Findings About Test Name FALNKID (String): Link ID FALNKGRP (String): Link Group ID FATESTCD (String): Findings About Test Short Name FAOBJ (String): Object of the Observation FASTAT (String): Completion Status FAREASND (String): Reason Not Performed FAEVAL (String): Evaluator EPOCH (String): Epoch FAEVINTX (String): Evaluation Interval Text EXDOSE (Float64): Dose EXTRT (String): Name of Treatment EXSTDTC (String): Start Date/Time of Treatment EXENDTC (String): End Date/Time of Treatment FAORRES (String): Result or Finding in Original Units VAX01DT (Date): Vaccination Date 01 VAX02DT (Date): Vaccination Date 02 EVENTFL (String): Event Value Flag EVENTDFL (String): Day Event Value Flag pharmaverseadam.adface_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adis_vaccine adis_vaccine - Immunogenicity Specimen Assessments ADaM (pharmaverse), from pharmaverseadam (). 64 rows x 103 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (Float64): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (Date): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation DTHDTC (String): Date/Time of Death DTHFL (String): Subject Death Flag REGION1 (String): Geographic Region 1 BRTHDTC (String): Date/Time of Birth DMDTC (String): Date/Time of Collection DMDY (Int32): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag PPROTFL (String): Per-Protocol Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRTP (String): Planned Treatment TRTA (String): Actual Treatment TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRT02P (String): Planned Treatment for Period 02 TRT02A (String): Actual Treatment for Period 02 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment AP01SDT (Date): Period 01 Start Date AP01EDT (Date): Period 01 End Date AP02SDT (Date): Period 02 Start Date AP02EDT (Date): Period 02 End Date APERSDT (Date): Period Start Date APEREDT (Date): Period End Date RFICDTC (String): Date/Time of Informed Consent ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ATPT (String): Analysis Timepoint ATPTN (Float64): Analysis Timepoint (N) ATPTREF (String): Analysis Timepoint Reference APERIOD (Int32): Period PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 AVAL (Float64): Analysis Value AVALU (String): Analysis Value Unit BASE (Float64): Baseline Value BASECAT1 (String): Baseline Category 1 BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline R2BASE (Float64): Ratio to Baseline CRIT1 (String): Analysis Criterion 1 CRIT1FL (String): Criterion 1 Evaluation Result Flag CRIT1FN (Int32): Criterion 1 Evaluation Result Flag (N) DTYPE (String): Derivation Type ABLFL (String): Baseline Record Flag ISSEQ (Float64): Sequence Number ISTESTCD (String): Immunogenicity Test/Exam Short Name ISTEST (String): Immunogenicity Test or Examination Name ISCAT (String): Category for Immunogenicity Test ISORRES (String): Results or Findings in Original Units ISORRESU (String): Original Units ISSTRESC (String): Character Result/Finding in Std Format ISSTRESN (Float64): Numeric Results/Findings in Std. Units ISSTRESU (String): Standard Units ISSTAT (String): Completion Status ISREASND (String): Reason Not Done ISNAM (String): Vendor Name ISSPEC (String): Specimen Type ISMETHOD (String): Method of Test or Examination ISBLFL (String): Baseline Flag ISLLOQ (Float64): Lower Limit of Quantitation VISITNUM (Float64): Visit Number EPOCH (String): Epoch ISDTC (String): Date/Time of Collection ISDY (String): Study Day of Visit/Collection/Exam ISULOQ (Float64): Upper Limit of Quantitation LOD (String): Limit of Detection DERIVED (String): Derivation Method CUTOFF02 (Float64): First Cutoff Value CUTOFF03 (Float64): Second Cutoff Value SERCAT1 (String): Pre-vaccination seropositivity status SERCAT1N (Float64): Pre-vaccination sero status (n) PPSRFL (String): Per-Protocol Record-Level Flag INVID (Float64): Investigator Identifier INVNAM (String): Investigator Name VAX01DT (Date): Vaccination Date 01 VAX02DT (Date): Vaccination Date 02 pharmaverseadam.adis_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adlb adlb - Laboratory Analysis ADaM (pharmaverse), from pharmaverseadam (). 83652 rows x 115 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRTP (String): Planned Treatment TRTA (String): Actual Treatment TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) BASE (Float64): Baseline Value BASEC (String): Baseline Value (C) BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline R2BASE (Float64): Ratio to Baseline R2ANRLO (Float64): Ratio of Analysis Val compared to ANRLO R2ANRHI (Float64): Ratio of Analysis Val compared to ANRHI SHIFT1 (String): Shift from Baseline to Analysis Value SHIFT2 (String): Shift from Baseline to Overall Grade DTYPE (String): Derivation Type ATOXGR (String): Analysis Toxicity Grade BTOXGR (String): Baseline Toxicity Grade ANRIND (String): Analysis Reference Range Indicator BNRIND (String): Baseline Reference Range Indicator ANRLO (Float64): Analysis Normal Range Lower Limit ANRHI (Float64): Analysis Normal Range Upper Limit ATOXGRL (String): Analysis Toxicity Grade Low ATOXGRH (String): Analysis Toxicity Grade High BTOXGRL (String): Baseline Toxicity Grade Low BTOXGRH (String): Baseline Toxicity Grade High ATOXDSCL (String): Analysis Toxicity Description Low ATOXDSCH (String): Analysis Toxicity Description High ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ONTRTFL (String): On Treatment Record Flag LVOTFL (String): Last Value On Treatment Record Flag LBSEQ (Float64): Sequence Number LBTESTCD (String): Lab Test or Examination Short Name LBTEST (String): Lab Test or Examination Name LBCAT (String): Category for Lab Test LBORRES (String): Result or Finding in Original Units LBORRESU (String): Original Units LBORNRLO (String): Reference Range Lower Limit in Orig Unit LBORNRHI (String): Reference Range Upper Limit in Orig Unit LBSTRESC (String): Character Result/Finding in Std Format LBSTRESN (Float64): Numeric Result/Finding in Standard Units LBSTRESU (String): Standard Units LBSTNRLO (Float64): Reference Range Lower Limit-Std Units LBSTNRHI (Float64): Reference Range Upper Limit-Std Units LBNRIND (String): Reference Range Indicator LBBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit LBDTC (String): Date/Time of Specimen Collection LBDY (Float64): Study Day of Specimen Collection pharmaverseadam.adlb_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adlb_metabolic adlb_metabolic - Laboratory Analysis for Metabolic ADaM (pharmaverse), from pharmaverseadam (). 371 rows x 43 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier DOMAIN (String): Domain Abbreviation TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 PARCAT2 (String): Parameter Category 2 AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) ANRLO (Float64): Analysis Normal Range Lower Limit ANRHI (Float64): Analysis Normal Range Upper Limit LBSEQ (Int32): Sequence Number LBTESTCD (String): Lab Test or Examination Short Name LBTEST (String): Lab Test or Examination Name LBCAT (String): Category for Lab Test LBORRES (String): Result or Finding in Original Units LBORRESU (String): Original Units LBORNRLO (String): Reference Range Lower Limit in Orig Unit LBORNRHI (String): Reference Range Upper Limit in Orig Unit LBSTRESC (String): Character Result/Finding in Std Format LBSTRESN (Float64): Numeric Result/Finding in Standard Units LBSTRESU (String): Standard Units LBSTNRLO (Float64): Reference Range Lower Limit-Std Units LBSTNRHI (Float64): Reference Range Upper Limit-Std Units LBNRIND (String): Reference Range Indicator LBBLFL (String): Baseline Flag LBFAST (String): Fasting Status VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit LBDTC (String): Date/Time of Specimen Collection LBDY (Float64): Study Day of Specimen Collection BMI (Float64): Body Mass Index (kg/m2) WSTCIR (Float64): Waist Circumference (cm) pharmaverseadam.adlb_metabolic_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adlb_neuro adlb_neuro - Laboratory Analysis for Neuroscience ADaM (pharmaverse), from pharmaverseadam (). 185 rows x 48 columns. Structure: One or more records per subject per analysis parameter per analysis visit. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier DOMAIN (String): Domain Abbreviation TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) ANRLO (Float64): Analysis Normal Range Lower Limit ANRHI (Float64): Analysis Normal Range Upper Limit BASE (Float64): Baseline Value BASEC (String): Baseline Value (C) BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ANL02FL (String): Analysis Flag 02 ONTRTFL (String): On Treatment Record Flag ASEQ (Int32): Analysis Sequence Number LBSEQ (Int32): Sequence Number LBTESTCD (String): Lab Test or Examination Short Name LBTEST (String): Lab Test or Examination Name LBCAT (String): Category for Lab Test LBORRES (String): Result or Finding in Original Units LBORRESU (String): Original Units LBORNRLO (String): Reference Range Lower Limit in Orig Unit LBORNRHI (String): Reference Range Upper Limit in Orig Unit LBSTRESC (String): Character Result/Finding in Std Format LBSTRESN (Float64): Numeric Result/Finding in Standard Units LBSTRESU (String): Standard Units LBSTNRLO (Float64): Reference Range Lower Limit-Std Units LBSTNRHI (Float64): Reference Range Upper Limit-Std Units LBNRIND (String): Reference Range Indicator LBBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit LBDTC (String): Date/Time of Specimen Collection LBDY (Float64): Study Day of Specimen Collection pharmaverseadam.adlb_neuro_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adlbhy adlbhy - Analysis of Lab Hy's Law ADaM (pharmaverse), from pharmaverseadam (). 251 rows x 14 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier TRT01A (String): Actual Treatment for Period 01 ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit PARAM (String): Parameter PARAMCD (String): Parameter Code AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) CRIT1 (String): Analysis Criterion 1 CRIT1FL (String): Criterion 1 Evaluation Result Flag ANRHI (Float64): Analysis Normal Range Upper Limit LBSEQ (Float64): Sequence Number pharmaverseadam.adlbhy_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.admh admh - Medical History Analysis ADaM (pharmaverse), from pharmaverseadam (). 1818 rows x 114 columns. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRTP (String): Planned Treatment TRTA (String): Actual Treatment TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Treatment End Datetime Imput Flag APHASE (String): Phase APHASEN (Float64): Description of Phase N EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 MHSEQ (Float64): Sequence Number MHTERM (String): Reported Term for the Medical History MHTERMN (Float64): Medical History Term (N) MHDECOD (String): Dictionary-Derived Term MHBODSYS (String): Body System or Organ Class MHLLT (String): Lowest Level Term MHHLT (String): High Level Term MHHLGT (String): High Level Group Term MHCAT (String): Category for Medical History MHSTDTC (String): Start Date/Time of Medical History Event ASTDT (Date): Analysis Start Date MHENDTC (String): End Date/Time of Medical History Event AENDT (Date): Analysis End Date ASTDY (Float64): Analysis Start Relative Day AENDY (Float64): Analysis End Relative Day MHOCCUR (String): Medical History Occurrence MHPRESP (String): Medical History Event Pre-Specified ANL01FL (String): Analysis Flag 01 AOCCFL (String): 1st Occurrence within Subject Flag AOCCPFL (String): 1st Occurrence of Preferred Term Flag AOCCSFL (String): 1st Occurrence of SOC Flag MHSPID (String): Sponsor-Defined Identifier MHSEV (String): Severity/Intensity VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit MHDTC (String): Date/Time of History Collection MHDY (Float64): Study Day of History Collection MHSTRTPT (String): Start Relative to Reference Time Point MHENRTPT (String): End Relative to Reference Time Point MHSTTPT (String): Start Reference Time Point MHENTPT (String): End Reference Time Point MHENRF (String): End Relative to Reference Period MHSTAT (String): Completion Status ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day SMQ02NAM (String): SMQ 02 Name SMQ02CD (Int32): SMQ 02 Code SMQ02SC (String): SMQ 02 Scope SMQ02SCN (Int32): SMQ 02 Scope (N) SMQ03NAM (String): SMQ 03 Name SMQ03CD (Int32): SMQ 03 Code SMQ03SC (String): SMQ 03 Scope SMQ03SCN (Int32): SMQ 03 Scope (N) SMQ05NAM (String): SMQ 05 Name SMQ05CD (Int32): SMQ 05 Code SMQ05SC (String): SMQ 05 Scope SMQ05SCN (Int32): SMQ 05 Scope (N) CQ01NAM (String): Customized Query 01 Name CQ04NAM (String): Customized Query 04 Name CQ04CD (Int32): Customized Query 04 Code AHIST (String): Response of Med Hx (past or current) AOCPFL (String): 1st Occur w/in Trt Prd FL AOCPSFL (String): 1st Occur of SOC w/in Trt Prd FL AOCPPFL (String): 1st Occur of PT w/in Trt Prd FL pharmaverseadam.admh_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adnv_neuro adnv_neuro - Nervous System Analysis Dataset ADaM (pharmaverse), from pharmaverseadam (). 30 rows x 43 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier DOMAIN (String): Domain Abbreviation ASEQ (Int32): Analysis Sequence Number AGE (Float64): Age SEX (String): Sex TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) PARAMN (Float64): Parameter (N) PARAM (String): Parameter PARAMCD (String): Parameter Code AVAL (Float64): Analysis Value BASE (Float64): Baseline Value BASETYPE (String): Baseline Type CRIT1 (String): Analysis Criterion 1 CRIT1FL (String): Criterion 1 Evaluation Result Flag ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ANL02FL (String): Analysis Flag 02 NVSEQ (Int32): Sequence Number NVLNKID (Float64): Link ID NVTESTCD (String): Short Name of Nervous System Test NVTEST (String): Name of Nervous System Test NVCAT (String): Category for Nervous System Test NVLOC (String): Location Used for the Measurement NVNAM (String): Vendor Name NVORRES (String): Result or Finding in Original Units NVORRESU (String): Original Units NVSTRESC (String): Character Result/Finding in Std Format NVSTRESN (Float64): Numeric Result/Finding in Standard Units NVSTRESU (String): Standard Units NVMETHOD (String): Method of Test or Examination NVLOBXFL (String): Last Observation Before Exposure Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name NVDTC (String): Date/Time of Collection NVDY (Float64): Study Day of Visit/Collection/Exam pharmaverseadam.adnv_neuro_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adoe_ophtha adoe_ophtha - Exam Analysis for Ophthalmology ADaM (pharmaverse), from pharmaverseadam (). 19136 rows x 103 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ATPT (String): Analysis Timepoint ATPTN (Float64): Analysis Timepoint (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) AVALU (String): Analysis Value Unit BASE (Float64): Baseline Value BASEC (String): Baseline Value (C) BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline DTYPE (String): Derivation Type ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ANL02FL (String): Analysis Flag 02 ONTRTFL (String): On Treatment Record Flag OESEQ (Int32): Sequence Number OECAT (String): Category for Ophthalmic Test or Exam OESCAT (String): Subcategory for Ophthalmic Test or Exam OEDTC (String): Date/Time of Collection VISIT (String): Visit Name VISITNUM (Float64): Visit Number VISITDY (Float64): Planned Study Day of Visit OESTRESN (Float64): Numeric Result/Finding in Standard Units OESTRESC (String): Character Result/Finding in Std Format OEORRES (String): Result or Finding in Original Units OETEST (String): Name of Ophthalmic Test or Exam OETESTCD (String): Short Name of Ophthalmic Test or Exam OETSTDTL (String): Ophthalmic Test or Exam Detail OELAT (String): Laterality OELOC (String): Location Used for the Measurement OEDY (Float64): Study Day of Visit/Collection/Exam OEMETHOD (String): Method of Test or Examination OEORRESU (String): Original Units OESTRESU (String): Standard Units OESTAT (String): Completion Status OETPT (String): Planned Time Point Name OETPTNUM (Float64): Planned Time Point Number STUDYEYE (String): Study Eye Location AFEYE (String): Affected Eye WORS01FL (String): Worst Post Baseline Obs pharmaverseadam.adoe_ophtha_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adpc adpc - Pharmacokinetic Concentrations ADaM (pharmaverse), from pharmaverseadam (). 4479 rows x 128 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Under 30 Group DTHA30FL (String): Over 30 Group DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Over 30 plus 30 days Group ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 DOSEP (Float64): Planned Treatment Dose DOSEA (Float64): Actual Treatment Dose DOSEU (String): Treatment Dose Units ADT (Date): Analysis Date ATM (Time): Analysis Time ADTM (Datetime): Analysis Datetime ADY (Float64): Analysis Relative Day ATMF (String): Analysis Time Imputation Flag ASTDT (Date): Analysis Start Date ASTTM (Time): Analysis Start Time ASTDTM (Datetime): Analysis Start Datetime AENDT (Date): Analysis End Date AENTM (Time): Analysis End Time AENDTM (Datetime): Analysis End Datetime AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ATPT (String): Analysis Timepoint ATPTN (Float64): Analysis Timepoint (N) ATPTREF (String): Analysis Timepoint Reference PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 AVAL (Float64): Analysis Value AVALU (String): Analysis Value Unit AVALCAT1 (String): Analysis Value Category 1 BASE (Float64): Baseline Value BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline DTYPE (String): Derivation Type ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ANL02FL (String): Analysis Flag 02 SRCDOM (String): Source Data SRCVAR (String): Source Variable SRCSEQ (Float64): Source Sequence Number NFRLT (Float64): Nom. Rel. Time from Analyte First Dose PCTESTCD (String): Pharmacokinetic Test Short Name PCTEST (String): Pharmacokinetic Test Name PCORRES (String): Result or Finding in Original Units PCORRESU (String): Original Units PCSTRESC (String): Character Result/Finding in Std Format PCSTRESN (Float64): Numeric Result/Finding in Standard Units PCSTRESU (String): Standard Units PCNAM (String): Vendor Name PCSPEC (String): Specimen Material Type PCLLOQ (Float64): Lower Limit of Quantitation VISIT (String): Visit Name VISITNUM (Float64): Visit Number VISITDY (Float64): Planned Study Day of Visit PCDTC (String): Date/Time of Specimen Collection PCDY (Float64): Actual Study Day of Specimen Collection PCTPT (String): Planned Time Point Name PCTPTNUM (Float64): Planned Time Point Number FANLDTM (Datetime): First Datetime of Dose for Analyte AFRLT (Float64): Act. Rel. Time from Analyte First Dose ARRLT (Float64): Actual Rel. Time from Ref. Dose PCRFTDTM (Datetime): Reference Datetime of Dose for Analyte FANLDT (Date): First Date of Dose for Analyte FANLTM (Time): First Time of Dose for Analyte PCRFTDT (Date): Reference Date of Dose for Analyte PCRFTTM (Time): Reference Time of Dose for Analyte NRRLT (Float64): Nominal Rel. Time from Ref. Dose FRLTU (String): Rel. Time from First Dose Unit RRLTU (String): Rel. Time from Ref. Dose Unit ALLOQ (Float64): Analysis Lower Limit of Quantitation MRRLT (Float64): Modified Rel. Time from Ref. Dose HTBL (Float64): Numeric Result/Finding in Standard Units HTBLU (String): Standard Units WTBL (Float64): Numeric Result/Finding in Standard Units WTBLU (String): Standard Units BMIBL (Float64): Baseline Body Mass Index (kg/m2) BMIBLU (String): BMI at Baseline (Unit) pharmaverseadam.adpc_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adpp adpp - Pharmacokinetic Parameters ADaM (pharmaverse), from pharmaverseadam (). 2688 rows x 79 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRTP (String): Planned Treatment TRTA (String): Actual Treatment TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) PARAMCD (String): Parameter Code AVAL (Float64): Numeric Result/Finding in Standard Units AVALCAT1 (String): Analysis Value Category 1 AVALCA1N (Float64): Analysis Value Category 1 (N) SRCDOM (String): Domain Abbreviation SRCVAR (String): Source Variable SRCSEQ (Int32): Sequence Number PPTESTCD (String): Parameter Short Name PPTEST (String): Parameter Name PPCAT (String): Parameter Category PPORRES (Float64): Result or Finding in Original Units PPORRESU (String): Original Units PPSTRESU (String): Standard Units PPSPEC (String): Specimen Material Type PPRFDTC (String): Date/Time of Reference Point VISIT (String): Visit Name VISITNUM (Float64): Visit Number PARCAT1 (String): Parameter Category AVALU (String): Standard Units pharmaverseadam.adpp_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adppk adppk - Population Pharmacokinetic ADaM (pharmaverse), from pharmaverseadam (). 3522 rows x 61 columns. Variables --------- PROJID (String): Project Identifier PROJIDN (Float64): Project Identifier (N) STUDYID (String): Study Identifier STUDYIDN (Float64): Study Identifier (N) USUBJID (String): Unique Subject Identifier USUBJIDN (Float64): Unique Subject Identifier (N) SUBJID (String): Subject Identifier for the Study SUBJIDN (Float64): Subject Identifier for the Study (N) SITEID (String): Study Site Identifier SITEIDN (Float64): Study Site Identifier (N) RECSEQ (Int32): Record Sequence AFRLT (Float64): Act. Rel. Time from Analyte First Dose APRLT (Float64): Actual Rel Time from Previous Dose NFRLT (Float64): Nom. Rel. Time from Analyte First Dose NPRLT (Float64): Nominal Rel Time from Previous Dose EVID (Float64): Event ID CMT (Float64): Compartment DV (Float64): Dependent Variable Result PARAMCD (String): Parameter Code PARAM (String): Parameter PARAMN (Float64): Parameter (N) ASEQ (Int32): Analysis Sequence Number AVAL (Float64): Analysis Value AVALU (String): Analysis Value Unit MDV (Float64): Missing Dependent Variable Result ALLOQ (Float64): Analysis Lower Limit of Quantitation BLQFL (String): Below Lower Limit of Quant Flag BLQFN (Float64): Below Lower Limit of Quant Flag (N) AMT (Float64): Actual Amount of Dose Received (unit) DOSEA (Float64): Actual Treatment Dose II (Float64): Dosing Interval (unit) SS (Float64): Steady State FORM (String): Drug Formulation FORMN (Float64): Drug Formulation (N) ROUTE (String): Route of Administration ROUTEN (Float64): Route of Administration (N) COHORT (Float64): Cohort Subject Enrolled Into COHORTC (String): Description of Planned Arm UDTC (String): Date/Time WTBL (Float64): Numeric Result/Finding in Standard Units HTBL (Float64): Numeric Result/Finding in Standard Units BMIBL (Float64): Baseline Body Mass Index (kg/m2) BSABL (Float64): Numeric Result/Finding in Standard Units AGE (Float64): Age SEX (String): Sex SEXN (Float64): Sex (N) RACE (String): Race RACEN (Float64): Race (N) ETHNIC (String): Ethnicity ETHNICN (Float64): Ethnicity (N) COUNTRY (String): Country COUNTRYL (String): Country Name COUNTRYN (Float64): Country (N) CREATBL (Float64): Numeric Result/Finding in Standard Units CRCLBL (Float64): Baseline Creatinine Clearance EGFRBL (Float64): Age TBILBL (Float64): Numeric Result/Finding in Standard Units ASTBL (Float64): Numeric Result/Finding in Standard Units ALTBL (Float64): Numeric Result/Finding in Standard Units DOSEP (Float64): Planned Treatment Dose DVL (Float64): Log DV pharmaverseadam.adppk_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adrs_onco adrs_onco - Tumor Response Analysis ADaM (pharmaverse), from pharmaverseadam (). 3694 rows x 79 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 ADT (Date): Analysis Date ADTF (String): Analysis Date Imputation Flag AVISIT (String): Analysis Visit PARAM (String): Parameter PARAMCD (String): Parameter Code PARCAT1 (String): Parameter Category 1 PARCAT2 (String): Parameter Category 2 PARCAT3 (String): Parameter Category 3 AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) ANL01FL (String): Analysis Flag 01 ANL02FL (String): Analysis Flag 02 VISITNUM (Float64): Visit Number VISIT (String): Visit Name RSTESTCD (String): Assessment Short Name RSTEST (String): Assessment Name RSORRES (String): Result or Finding in Original Units RSSTRESC (String): Character Result/Finding in Std Format RSEVAL (String): Evaluator RSEVALID (String): Evaluator Identifier RSACPTFL (String): Accepted Record Flag RSDTC (String): Date/Time of Assessment RSSEQ (Int32): Sequence Number DTHDTF (String): Date of Death Imputation Flag pharmaverseadam.adrs_onco_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adsl adsl - Subject Level Analysis ADaM (pharmaverse), from pharmaverseadam (). 306 rows x 55 columns. Structure: One record per subject. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 BRTHDTC (String): Date/Time of Birth pharmaverseadam.adsl_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adsl_vaccine adsl_vaccine - Subject Level Analysis for Vaccine ADaM (pharmaverse), from pharmaverseadam (). 2 rows x 46 columns. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (Float64): Study Site Identifier COUNTRY (String): Country/Region RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation DTHDTC (String): Date/Time of Death DTHFL (String): Subject Death Flag REGION1 (String): Geographic Region 1 BRTHDTC (String): Date/Time of Birth DMDTC (String): Date/Time of Collection DMDY (Int32): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag PPROTFL (String): Per-Protocol Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRT02P (String): Planned Treatment for Period 02 TRT02A (String): Actual Treatment for Period 02 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment AP01SDT (Date): Period 01 Start Date AP01EDT (Date): Period 01 End Date AP02SDT (Date): Period 02 Start Date AP02EDT (Date): Period 02 End Date RFICDTC (String): Date/Time of Informed Consent INVID (Float64): Investigator Identifier INVNAM (String): Investigator Name VAX01DT (Date): Vaccination Date 01 VAX02DT (Date): Vaccination Date 02 pharmaverseadam.adsl_vaccine_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adtpet_neuro adtpet_neuro - Tau PET Scan Analysis Dataset ADaM (pharmaverse), from pharmaverseadam (). 34 rows x 46 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier DOMAIN (String): Domain Abbreviation ASEQ (Int32): Analysis Sequence Number TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTEDT (Date): Date of Last Exposure to Treatment ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) PARAM (String): Parameter PARAMCD (String): Parameter Code AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) BASE (Float64): Baseline Value BASEC (String): Baseline Value (C) BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ANL02FL (String): Analysis Flag 02 ONTRTFL (String): On Treatment Record Flag NVSEQ (Int32): Sequence Number NVLNKID (Float64): Link ID NVTESTCD (String): Short Name of Nervous System Test NVTEST (String): Name of Nervous System Test NVCAT (String): Category for Nervous System Test NVLOC (String): Location Used for the Measurement NVNAM (String): Vendor Name NVORRES (String): Result or Finding in Original Units NVORRESU (String): Original Units NVSTRESC (String): Character Result/Finding in Std Format NVSTRESN (Float64): Numeric Result/Finding in Standard Units NVSTRESU (String): Standard Units NVMETHOD (String): Method of Test or Examination NVLOBXFL (String): Last Observation Before Exposure Flag REFREG (String): Reference Region AGTRT (String): Reported Agent Name AGCAT (String): Category for Agent VISITNUM (Float64): Visit Number VISIT (String): Visit Name NVDTC (String): Date/Time of Collection NVDY (Float64): Study Day of Visit/Collection/Exam pharmaverseadam.adtpet_neuro_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adtr_onco adtr_onco - Tumor Results Analysis for Oncology ADaM (pharmaverse), from pharmaverseadam (). 181 rows x 99 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag PDFL (String): Pharmacodynamic Analysis Set Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day ADTF (String): Analysis Date Imputation Flag AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARCAT1 (String): Parameter Category 1 PARCAT2 (String): Parameter Category 2 PARCAT3 (String): Parameter Category 3 AVAL (Float64): Analysis Value BASE (Float64): Baseline Value CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline NADIR (Float64): NADIR CHGNAD (Float64): Change from NADIR PCHGNAD (Float64): Percent Change from NADIR ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ANL02FL (String): Analysis Flag 02 ANL03FL (String): Analysis Flag 03 ANL04FL (String): Analysis Flag 04 TRSEQ (Int32): Sequence Number TRGRPID (String): Group ID TRLNKID (String): Link ID TRTESTCD (String): Tumor/Lesion Assessment Short Name TRTEST (String): Tumor/Lesion Assessment Test Name TRORRES (String): Result or Finding in Original Units TRORRESU (String): Original Units TRSTRESC (String): Character Result/Finding in Std Format TRSTRESN (Float64): Numeric Result/Finding in Standard Units TRSTRESU (String): Standard Units TREVAL (String): Evaluator TREVALID (String): Evaluator Identifier TRACPTFL (String): Accepted Record Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name TRDTC (String): Date/Time of Tumor/Lesion Measurement TULOC (String): Location of the Tumor/Lesion TULOCGR1 (String): Tumor Site Group 1 LSEXP (String): Lesion IDs Expected LSASS (String): Lesion IDs Assessed DTHDTF (String): Date of Death Imputation Flag pharmaverseadam.adtr_onco_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.adtte_onco adtte_onco - Time to Event Analysis for Oncology ADaM (pharmaverse), from pharmaverseadam (). 512 rows x 20 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier ASEQ (Int32): Analysis Sequence Number AGE (Float64): Age SEX (String): Sex ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code ADT (Date): Analysis Date PARAM (String): Parameter PARAMCD (String): Parameter Code AVAL (Float64): Analysis Value STARTDT (Date): Time-to-Event Origin Date for Subject CNSR (Int32): Censor EVNTDESC (String): Event or Censoring Description CNSDTDSC (String): Censor Date Description SRCDOM (String): Source Data SRCVAR (String): Source Variable SRCSEQ (Int32): Source Sequence Number pharmaverseadam.adtte_onco_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.advfq_ophtha advfq_ophtha - Visual Function Questionnaire Analysis ADaM (pharmaverse), from pharmaverseadam (). 28798 rows x 89 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (String): Analysis Visit (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARCAT1 (String): Parameter Category 1 PARCAT2 (String): Parameter Category 2 AVAL (Float64): Analysis Value AVALC (String): Analysis Value (C) BASE (Float64): Baseline Value CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ONTRTFL (String): On Treatment Record Flag QSSEQ (Int32): Sequence Number QSTESTCD (String): Question Short Name QSTEST (String): Question Name QSCAT (String): Category of Question QSSCAT (String): Subcategory for Question QSORRES (String): Finding in Original Units QSORRESU (String): Original Units QSSTRESC (String): Character Result/Finding in Std Format QSSTRESN (Float64): Numeric Finding in Standard Units QSSTRESU (String): Standard Units QSBLFL (String): Baseline Flag QSDRVFL (String): Derived Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit QSDTC (String): Date/Time of Finding QSDY (Float64): Study Day of Finding pharmaverseadam.advfq_ophtha_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.advs advs - Vital Signs Analysis ADaM (pharmaverse), from pharmaverseadam (). 65032 rows x 105 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRTP (String): Planned Treatment TRTA (String): Actual Treatment TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ATPT (String): Analysis Timepoint ATPTN (Float64): Analysis Timepoint (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) AVAL (Float64): Analysis Value AVALCAT1 (String): Analysis Value Category 1 AVALCA1N (Float64): Analysis Value Category 1 (N) BASE (Float64): Baseline Value BASETYPE (String): Baseline Type CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline DTYPE (String): Derivation Type ANRIND (String): Analysis Reference Range Indicator BNRIND (String): Baseline Reference Range Indicator ANRLO (Float64): Analysis Normal Range Lower Limit ANRHI (Float64): Analysis Normal Range Upper Limit A1LO (Float64): Analysis Range 1 Lower Limit A1HI (Float64): Analysis Range 1 Upper Limit ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ONTRTFL (String): On Treatment Record Flag VSSEQ (Float64): Sequence Number VSTESTCD (String): Vital Signs Test Short Name VSTEST (String): Vital Signs Test Name VSPOS (String): Vital Signs Position of Subject VSORRES (String): Result or Finding in Original Units VSORRESU (String): Original Units VSSTRESC (String): Character Result/Finding in Std Format VSSTRESN (Float64): Numeric Result/Finding in Standard Units VSSTRESU (String): Standard Units VSSTAT (String): Completion Status VSLOC (String): Location of Vital Signs Measurement VSBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit VSDTC (String): Date/Time of Measurements VSDY (Float64): Study Day of Vital Signs VSTPT (String): Planned Time Point Name VSTPTNUM (Float64): Planned Time Point Number VSELTM (String): Planned Elapsed Time from Time Point Ref VSTPTREF (String): Time Point Reference pharmaverseadam.advs_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.advs_metabolic advs_metabolic - Vital Signs Analysis for Metabolic ADaM (pharmaverse), from pharmaverseadam (). 760 rows x 101 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation SCRFDT (Date): Screen Failure Date FRVDT (Date): Final Retrieval Visit Date DTHDTC (String): Date/Time of Death DTHADY (Float64): Relative Day of Death DTHFL (String): Subject Death Flag LDDTHELD (Float64): Elapsed Days from Last Dose to Death LDDTHGR1 (String): Last Dose to Death - Days Elapsed Grp 1 DTH30FL (String): Death Within 30 Days of Last Trt Flag DTHA30FL (String): Death After 30 Days from Last Trt Flag DTHDOM (String): Domain for Date of Death Collection DTHB30FL (String): Death Within 30 Days of First Trt Flag ASEQ (Int32): Analysis Sequence Number REGION1 (String): Geographic Region 1 DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units AGEGR1 (String): Pooled Age Group 1 SEX (String): Sex RACE (String): Race RACEGR1 (String): Pooled Race Group 1 ETHNIC (String): Ethnicity SAFFL (String): Safety Population Flag ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag EOSSTT (String): End of Study Status EOSDT (Date): End of Study Date RFICDTC (String): Date/Time of Informed Consent RANDDT (Date): Date of Randomization LSTALVDT (Date): Date Last Known Alive TRTDURD (Float64): Total Treatment Duration (Days) DTHDT (Date): Date of Death DTHDTF (String): Date of Death Imputation Flag DTHCAUS (String): Cause of Death DTHCGR1 (String): Cause of Death Reason 1 ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ATPT (String): Analysis Timepoint ATPTN (Float64): Analysis Timepoint (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) PARCAT1 (String): Parameter Category 1 PARCAT1N (Float64): Parameter Category 1 (N) AVAL (Float64): Analysis Value AVALCAT1 (String): Analysis Value Category 1 AVALCA1N (Float64): Analysis Value Category 1 (N) BASE (Float64): Baseline Value BASECAT1 (String): Baseline Category 1 BASECA1N (Float64): Baseline Category 1 (N) CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline CRIT1 (String): Analysis Criterion 1 CRIT1FL (String): Criterion 1 Evaluation Result Flag CRIT2 (String): Analysis Criterion 2 CRIT2FL (String): Criterion 2 Evaluation Result Flag ABLFL (String): Baseline Record Flag VSSEQ (Int32): Sequence Number VSTESTCD (String): Vital Signs Test Short Name VSTEST (String): Vital Signs Test Name VSPOS (String): Vital Signs Position of Subject VSORRES (String): Result or Finding in Original Units VSORRESU (String): Original Units VSSTRESC (String): Character Result/Finding in Std Format VSSTRESN (Float64): Numeric Result/Finding in Standard Units VSSTRESU (String): Standard Units VSSTAT (String): Completion Status VSLOC (String): Location of Vital Signs Measurement VSBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Float64): Planned Study Day of Visit VSDTC (String): Date/Time of Measurements VSDY (Float64): Study Day of Vital Signs VSTPT (String): Planned Time Point Name VSTPTNUM (Float64): Planned Time Point Number VSELTM (String): Planned Elapsed Time from Time Point Ref VSTPTREF (String): Time Point Reference pharmaverseadam.advs_metabolic_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) pharmaverseadam.advs_peds advs_peds - Vital Signs Analysis for Pediatrics ADaM (pharmaverse), from pharmaverseadam (). 546 rows x 80 columns. Structure: One or more records per subject per analysis parameter per analysis timepoint. Variables --------- STUDYID (String): Study Identifier USUBJID (String): Unique Subject Identifier SUBJID (String): Subject Identifier for the Study SITEID (String): Study Site Identifier COUNTRY (String): Country DOMAIN (String): Domain Abbreviation RFSTDTC (String): Subject Reference Start Date/Time RFENDTC (String): Subject Reference End Date/Time RFXSTDTC (String): Date/Time of First Study Treatment RFXENDTC (String): Date/Time of Last Study Treatment RFPENDTC (String): Date/Time of End of Participation DTHDTC (String): Date/Time of Death DTHFL (String): Subject Death Flag ASEQ (Int32): Analysis Sequence Number BRTHDTC (String): Date/Time of Birth (Character) BRTHDT (Date): Date/Time of Birth DMDTC (String): Date/Time of Collection DMDY (Float64): Study Day of Collection AGE (Float64): Age AGEU (String): Age Units SEX (String): Sex RACE (String): Race ETHNIC (String): Ethnicity ARM (String): Description of Planned Arm ARMCD (String): Planned Arm Code ACTARM (String): Description of Actual Arm ACTARMCD (String): Actual Arm Code TRT01P (String): Planned Treatment for Period 01 TRT01A (String): Actual Treatment for Period 01 TRTSDT (Date): Date of First Exposure to Treatment TRTSDTM (Datetime): Datetime of First Exposure to Treatment TRTSTMF (String): Time of First Exposure Imput. Flag TRTEDT (Date): Date of Last Exposure to Treatment TRTEDTM (Datetime): Datetime of Last Exposure to Treatment TRTETMF (String): Time of Last Exposure Imput. Flag RFICDTC (String): Date/Time of Informed Consent TRTDURD (Float64): Total Treatment Duration (Days) ADT (Date): Analysis Date ADY (Float64): Analysis Relative Day AVISIT (String): Analysis Visit AVISITN (Float64): Analysis Visit (N) ATPT (String): Analysis Timepoint ATPTN (Float64): Analysis Timepoint (N) PARAM (String): Parameter PARAMCD (String): Parameter Code PARAMN (Float64): Parameter (N) AVAL (Float64): Analysis Value BASE (Float64): Baseline Value CHG (Float64): Change from Baseline PCHG (Float64): Percent Change from Baseline ABLFL (String): Baseline Record Flag ANL01FL (String): Analysis Flag 01 ONTRTFL (String): On Treatment Record Flag EPOCH (String): Epoch VSEVAL (String): Evaluator VSSEQ (Int32): Sequence Number VSTESTCD (String): Vital Signs Test Short Name VSTEST (String): Vital Signs Test Name VSPOS (String): Vital Signs Position of Subject VSORRES (String): Result or Finding in Original Units VSORRESU (String): Original Units VSSTRESC (String): Character Result/Finding in Std Format VSSTRESN (Float64): Numeric Result/Finding in Standard Units VSSTRESU (String): Standard Units VSSTAT (String): Completion Status VSLOC (String): Location of Vital Signs Measurement VSBLFL (String): Baseline Flag VISITNUM (Float64): Visit Number VISIT (String): Visit Name VISITDY (Int32): Planned Study Day of Visit VSDTC (String): Date/Time of Measurements VSDY (Int32): Study Day of Vital Signs VSTPT (String): Planned Time Point Name VSTPTNUM (Float64): Planned Time Point Number VSELTM (String): Planned Elapsed Time from Time Point Ref VSTPTREF (String): Time Point Reference AAGECUR (Float64): Current Analysis Age (Days) AAGECURU (String): Current Analysis Age Units HGTTMP (Float64): Temporary Height at Timepoint HGTTMPU (String): Temporary Height at Timepoint Units pharmaverseadam.advs_peds_meta Metadata of one dataset, in the style of pyreadstat's metadata object. A read-only view: the field names and parallel-tuple layout follow pyreadstat, extended with the CDISC dimensions (``structure``, ``mandatory``, ``role``). The data itself is reached through the module attribute of the same name (e.g. ``pharmaverseadam.adsl``). Attributes ---------- dataset : str The dataset name, e.g. ``"adsl"``. collection : str The collection it belongs to, e.g. ``"pharmaverseadam"``. file_label : str or None The dataset label, equivalent to a SAS dataset label. structure : str or None The CDISC structure, e.g. ``"One record per subject"``; None when the source specifications do not provide one. number_rows : int Row count, read from the parquet footer without loading any data. number_columns : int Column count, i.e. ``len(column_names)``. column_names : tuple of str The column names, in column order. column_labels : tuple of str or None The column labels, parallel to ``column_names``. column_types : tuple of str or None The column types, parallel to ``column_names``. column_mandatory : tuple of str or None The CDISC mandatory flags, parallel to ``column_names``. column_roles : tuple of str or None The CDISC roles, parallel to ``column_names``. file_format : str Always ``"parquet"``, the storage format of every dataset. file_encoding : str Always ``"utf-8"``: the encoding of the shipped parquet data, not of the original source file. Examples -------- >>> meta = pharmaverseadam.meta("adsl") >>> meta.dataset 'adsl' >>> meta.file_label 'Subject Level Analysis' >>> meta.column_names_to_labels["STUDYID"] 'Study Identifier' >>> (meta.number_rows, meta.number_columns) (306, 55) ---------------------------------------------------------------------- This is the User Guide documentation for the package. ---------------------------------------------------------------------- ### Getting started Datasets are module attributes, lazy-loaded from parquet. ## Collections | Module | Standard | Source | Datasets | | --- | --- | --- | --: | | `pharmadata.pharmaverseadam` | ADaM | pharmaverseadam | 30 | | `pharmadata.pharmaversesdtm` | SDTM | pharmaversesdtm | 64 | | `pharmadata.cdiscpilotadam` | ADaM | CDISC pilot | 12 | | `pharmadata.cdiscpilotsdtm` | SDTM | CDISC pilot | 31 | ## Install ```bash pip install pharmadata ``` ## Usage ```{python} import polars as pl from pharmadata import pharmaverseadam as adam, pharmaversesdtm as sdtm ``` ```{python} adam.list_datasets() adam.meta_tables() adam.meta_columns() adam.meta_specs() adam_dict = adam.to_dict() ``` ```{python} adsl = adam.adsl adsl_meta = adam.adsl_meta adsl_meta.column_names adsl_meta.column_labels adsl_meta.column_names_to_labels adsl_meta.number_rows adsl_meta.number_columns adsl_meta.file_label adsl_meta.file_encoding adsl.head() ``` ## Format ```{python} from pharmadata import set_output_pandas, set_output_polars, output_format set_output_pandas() dm = sdtm.dm print(type(dm)) set_output_polars() dm = sdtm.dm print(type(dm)) ``` `set_output_pandas()` / `set_output_polars()` switch globally; `output_format()` is a context manager. ```{python} with output_format("pandas"): adsl_pd = adam.adsl print(type(adsl_pd)) ``` ## Validate by `pointblank` ```{python} import pointblank as pb # pb.validate_adam(adsl, "ADSL") pb.validate_adam_structure(adsl, "ADSL") ``` ## Polars Examples ```{python} adsl.select(["STUDYID", "USUBJID", "AGE", "SEX", "TRT01A"]).head() ``` ```{python} adsl.filter((pl.col("AGE") >= 75) & (pl.col("SEX") == "F")).select( ["USUBJID", "AGE", "SEX", "TRT01A"] ).head() ``` ```{python} adsl.filter(pl.col("TRT01A") != "Screen Failure").group_by("TRT01A").agg( pl.col("AGE").mean().round(1).alias("mean_age"), pl.len().alias("n"), ).sort("TRT01A") ``` ## Read parquet directly - Dataset label in schema metadata - Column labels in field metadata. Both are bytes, decode to str ```{python} from importlib import resources import pyarrow.parquet as pq path = resources.files("pharmadata") / "_data" / "pharmaverseadam" / "adsl.parquet" schema = pq.ParquetFile(path).schema_arrow print((schema.metadata or {}).get(b"label", b"").decode()) print({ name: (schema.field(name).metadata or {}).get(b"label", b"").decode() for name in schema.names[:3] }) ``` ```{python} pl.from_arrow(pq.read_table(path, columns=schema.names[:6])).head(5) ```