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license: other
task_categories:
- tabular-classification
- tabular-regression
tags:
- courts
- federal-courts
- litigation
- criminal-justice
- fjc
- duckdb
- datapond
pretty_name: FJC Integrated Database (federal civil, criminal, appellate cases)
size_categories:
- 10M<n<100M
---
# FJC Integrated Database (IDB)
Every civil case (SY1988-present), criminal defendant (FY1970-present) and appeal
(1971-present) reported by the federal courts to the Administrative Office of the
U.S. Courts, as published in the Federal Judicial Center's Integrated Database
(updated quarterly). Column names are the IDB's; -8/-9 and 01/01/1900 sentinels
are stored as NULL.
**21,119,023 rows across 3 tables.**
| Table | Description | Row Count | Column Count |
|---|---|---|---|
| `civil` | Civil cases filed in U.S. district courts, statistical year 1988 to present: one row per case (parties, nature of suit, jurisdiction, filing/termination dates, disposition, judgment) | 10,959,535 | 47 |
| `criminal` | Criminal defendants in U.S. district courts, FY1970 to present: one row per defendant (filing offenses, disposition, sentence, dates) | 7,743,962 | 176 |
| `appellate` | Appeals filed in U.S. courts of appeals, 1971 to present: one row per appeal (origin, nature of suit/offense, disposition, dates, judges) | 2,415,526 | 71 |
## Query it remotely
```sql
INSTALL httpfs; LOAD httpfs;
ATTACH 'https://huggingface.co/datasets/Nason/fjc-database/resolve/main/fjc.duckdb' AS fjc (READ_ONLY);
SELECT EXTRACT(YEAR FROM FILEDATE) AS year, COUNT(*) AS civil_cases
FROM fjc.civil WHERE FILEDATE >= '2015-01-01'
GROUP BY 1 ORDER BY 1;
```
Or with the datapond packages: `pip install datapond` / `pak::pak("datapond-db/datapond-r")`.
Build pipeline, codebooks and caveats: https://github.com/ian-nason/fjc-database
Source: https://www.fjc.gov/research/idb (public domain).
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