One-time snapshot

FDA FAERS Drug Adverse Events 2023

Reconciled 2023 FAERS extract with 1,541,888 retained cases and seven related tables; supplied 2023 deletion lists applied.

Snapshot coverage

Records: 1,541,888 case rows; seven related tables

Coverage: 2023 Q1–Q4

Format: CSV + Parquet

Package uploaded: 2026-09-19

Listing reviewed: 2026-09-19

The upload and review dates do not extend the source coverage. This is a dated snapshot; future updates are not included.

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CSV and Parquet files for the coverage described here. Review the limitations and sample before purchasing.

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Known limitations

Historical 2023 Q1–Q4 quarterly-extract cohort, not a current database or a count of events first occurring in 2023. No later quarters or deletion lists are included.
Keeps the maximum case version observed per case within these four extracts. The union of their supplied deletion lists excludes 3,103 previously retained cases and their related rows.
All child records match the retained DEMO primaryid, caseid and extraction quarter. Reconciliation removed 2,819,928 child rows from superseded reports.
DRUG primaryid plus drug_seq identifies a drug group, not a unique row: FDA permits multiple dosing/route records. All 623 repeated groups (636 additional rows) are preserved. drug_record_id is unique only within this release.
INDI.indi_drug_seq and THER.dsg_drug_seq link to DRUG.drug_seq within primaryid. Join through distinct drug groups or aggregate first to avoid multiplying indication and therapy rows. Joining multiple child tables can also multiply records.
Reports do not establish causation, incidence rates or comparative drug safety. Reactions are report-level and cannot automatically be attributed to an individual drug.
Existing cleaned values, partial dates and substantial missingness are preserved. event_dt and mfr_dt remain numeric source-date fields; drug rechallenge is stored in rechal. Validation covers packaging and case/drug relationships, not clinical interpretation.

Files in this snapshot

Row counts are per table and should not be added as independent events. Expand a file to see its delivered Parquet field names and types.

fda_faers_demo.parquet — 1,541,888 rows · 31 fields

Field	Type
primaryid	string
caseid	string
caseversion	int64
i_f_code	string
event_dt	double
mfr_dt	double
init_fda_dt	string
fda_dt	string
rept_cod	string
auth_num	string
mfr_num	string
mfr_sndr	string
lit_ref	string
age	string
age_cod	string
age_grp	string
sex	string
e_sub	string
wt	string
wt_cod	string
rept_dt	string
to_mfr	string
occp_cod	string
reporter_country	string
occr_country	string
_quarter	string
age_years	double
sex_label	string
reporter_type	string
report_type	string
wt_kg	double

fda_faers_drug.parquet — 6,380,418 rows · 23 fields

Field	Type
primaryid	string
caseid	string
drug_seq	string
role_cod	string
drugname	string
prod_ai	string
val_vbm	int64
route	string
dose_vbm	string
cum_dose_chr	double
cum_dose_unit	string
dechal	string
rechal	string
lot_num	string
exp_dt	double
nda_num	string
dose_amt	double
dose_unit	string
dose_form	string
dose_freq	string
_quarter	string
drug_role	string
drug_record_id	int64

fda_faers_indi.parquet — 3,985,962 rows · 5 fields

Field	Type
primaryid	string
caseid	string
indi_drug_seq	int64
indi_pt	string
_quarter	string

fda_faers_outc.parquet — 1,133,087 rows · 5 fields

Field	Type
primaryid	string
caseid	string
outc_cod	string
_quarter	string
outcome	string

fda_faers_reac.parquet — 5,059,863 rows · 5 fields

Field	Type
primaryid	string
caseid	string
pt	string
drug_rec_act	string
_quarter	string

fda_faers_rpsr.parquet — 52,497 rows · 5 fields

Field	Type
primaryid	string
caseid	string
rpsr_cod	string
_quarter	string
report_source	string

fda_faers_ther.parquet — 2,183,196 rows · 9 fields

Field	Type
primaryid	string
caseid	string
dsg_drug_seq	int64
start_dt	string
end_dt	string
dur	string
dur_cod	string
_quarter	string
duration_unit	string

Inspect the public CSV

import pandas as pd

df = pd.read_csv(
    "https://huggingface.co/datasets/claritystorm/fda-faers-drug-adverse-events/resolve/main/sample_1000.csv"
)
print(df.shape)
print(df.columns.tolist())
print(df.head())

This CSV is a sample, not the full package. It does not establish complete historical coverage or represent every field’s missingness. License details are on the Hugging Face card.

Source: government source portal · Dataset changelog