from pharmadata import pharmaversesdtm
meta = pharmaversesdtm.meta('suppface_vaccine')
print(f"Rows: {meta.number_rows:,} Columns: {meta.number_columns}")Rows: 4 Columns: 9suppface_vaccine
suppface_vaccine
Supplemental Qualifiers for Findings About for Clinical Events for Vaccine
Variables
Show variable specs
shape: (9, 5)
| variable | label | type | mandatory | role |
|---|---|---|---|---|
| str | str | str | null | null |
| "STUDYID" | "Study Identifier" | "String" | null | null |
| "USUBJID" | "Unique Subject Identifier" | "String" | null | null |
| "RDOMAIN" | "Related Domain Abbreviation" | "String" | null | null |
| "IDVAR" | "Identifying Variable" | "String" | null | null |
| "IDVARVAL" | "Identifying Variable Value" | "String" | null | null |
| "QNAM" | "Qualifier Variable Name" | "String" | null | null |
| "QVAL" | "Data Value" | "String" | null | null |
| "QLABEL" | "Qualifier Variable Label" | "String" | null | null |
| "QORIG" | "Origin" | "String" | null | null |
Examples
from great_docs import tbl_explorer
from pharmadata import pharmaversesdtm
tbl_explorer(pharmaversesdtm.suppface_vaccine.head(10))PolarsRows4Columns9 | |||||||||
STUDYID str |
USUBJID str |
RDOMAIN str |
IDVAR str |
IDVARVAL str |
QNAM str |
QVAL str |
QLABEL str |
QORIG str |
|
|---|---|---|---|---|---|---|---|---|---|
| 0 | ABC | ABC-1001 | FACE | FASEQ | 1 | CLTYP | DAIRY | Collection Type | Predecessor |
| 1 | ABC | ABC-1001 | FACE | FASEQ | 2 | CLTYP | DAIRY | Collection Type | Predecessor |
| 2 | ABC | ABC-1002 | FACE | FASEQ | 1 | CLTYP | DAIRY | Collection Type | Predecessor |
| 3 | ABC | ABC-1002 | FACE | FASEQ | 2 | CLTYP | DAIRY | Collection Type | Predecessor |