fjc-idb

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What is fjc-idb?

fjc-idb turns the Federal Judicial Center's Integrated Database (IDB) into clean CSV files.

Why use fjc-idb?

• Readable columns. IDB field names such as PROCPROG become descriptive names such as procedural_progress, and codes become labels from the FJC codebooks (Ninth Circuit, Dismissed as settled, Los Angeles, CA).
• Correct missing data. The IDB's missing-value codes (-8 and the date 1900-01-01) become real missing values, with the exceptions the codebooks describe (such as civil in forma pauperis status, where -8 means "no").
• No double counting. Each yearly file repeats every case still pending when it was made. fjc-idb keeps pending cases only from the latest file, so combining years does not count a case more than once.
• Useful added columns. Indicators for appeal types and for groups of offenses and natures of suit, the days between key dates, counts of concurrences and dissents, a standard appellate docket number, and more.
• Large files, little memory. Years are processed one at a time, so even the criminal files (144 columns) need only a gigabyte or two of memory.
• Codebooks for the output. The documentation includes codebooks that describe every column of the CSV files and how it relates to the IDB.

The IDB is the most complete public source of case-level data on the federal courts, but it is distributed as one SAS file per year with confusing field names and a messy coding system. This repo addresses those shortcomings. But it cannot cure the issue of missing data (particularly judge names). However, the improvements made here should make it easier to merge the IDB data with other sources (using the standard docket number format in docket_number).

fjc-idb has been tested on the files from 2008 through 2026. It does not yet support the bankruptcy files or the older files that use older codebooks.

Getting started

Requirements

• Python 3.11 or later
• An internet connection to download the IDB files from the FJC IDB page, or the SAS (.sas7bdat) files themselves

Installation

To install fjc-idb, use pip:

pip install fjc-idb

The package is installed as fjc-idb and imported in Python as fjc_idb:

import fjc_idb

Usage

Download the yearly files from the FJC website and export them in one step:

fjc-idb appellate --start-year 2008 --stop-year 2026 --data-folder path/to/fjc_idb --download

--download fetches only the files the data folder does not already have, along with the FJC codebook for each case type. Use --download-only to fetch files without exporting, and --overwrite to replace files already downloaded (the FJC updates the file for the current year during the year). Once the files are downloaded, leave out --download to export them again:

fjc-idb all --start-year 2015 --data-folder path/to/fjc_idb

Or from Python:

import fjc_idb

fjc_idb.download('criminal', 2008, 2026, data_folder = 'path/to/fjc_idb')
fjc_idb.run('criminal', 2008, 2026, data_folder = 'path/to/fjc_idb')

The files are saved in this layout under their FJC names (such as ap08.sas7bdat or cv12_0.sas7bdat). Files you download yourself work the same way if you put them in the same folders:

fjc_idb/
├── appellate/          ap08.sas7bdat, ap09.sas7bdat, ...
├── district/
│   ├── civil/          cv08_0.sas7bdat, cv09_0.sas7bdat, ...
│   └── criminal/       cr08.sas7bdat, cr09.sas7bdat, ...
└── docs/               the FJC codebooks

Each case type is saved next to its yearly files as fjc_idb_{case_type}_data_{start_year}_{stop_year}.csv. Missing dates are written as NA, and other missing values are left blank.

See the documentation for a tutorial, codebooks for each case type, and example analyses.

Contributing

Contributors are always welcome. Feel free to grab an issue to work on or make a suggested improvement. If you wish to contribute, please read the Contribution Guide and Code of Conduct.

Related Projects

The Federal Judicial Center publishes the IDB, its codebooks, and an interactive tool for exploring the data.

License

Use of this repository is authorized under the Apache Software License 2.0.