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USSC Federal Sentencing Database

Every federal defendant sentenced from FY2002 through FY2025 (1.72M), from the U.S. Sentencing Commission's public individual offender datafiles: demographics, offense of conviction, guideline calculations, sentence imposed, departures and variances. The Commission's ~22,000-variable fixed-width layout is reshaped into a wide sentences table plus long tables per count of conviction, guideline computation, drug type and departure reason. 13,962,089 rows across 9 tables.

Table Description Row Count Column Count
new_statutes Statutes of conviction as recorded in NWSTAT slots 3,279,305 4
departure_reasons One row per stated reason for departure/variance: REAS code + RETEXT text (FY2004+, post-Booker coding) or REASON + REASTXT (FY2002-03, pre-Booker coding) 2,637,999 7
counts One row per count of conviction: statute (TTSC1/TTSC2/TTSC3 = title/section/subsection), statutory minimum/maximum (SMIN/SMAX) and STA1-3 2,412,926 11
sentences One row per federal defendant sentenced in the fiscal year: demographics, offense, guideline range, sentence imposed, departures (scalar variables of the USSC individual offender datafile) 1,720,684 1610
guidelines One row per guideline computation on the case: base offense level, specific offense characteristics and Chapter 3 adjustments (ADJ_*), per-guideline totals 1,706,580 348
drugs One row per drug type involved: type, weight, units, equivalency (DRUGTYP, WGT, UNIT, MWGT, DRGAM, ...) 749,098 14
pleas One row per plea/verdict slot (INPLEA, INNOPL) 738,024 5
offense_dates Offense begin/end dates per slot (OFBEG/OFEND; FY2002-era files only) 501,590 5
chapter_text Free-text chapter 2/3/4 guideline notes (CHP2TXT/CHP3TXT/CHP4TXT) and change flags 215,883 9

Query it remotely

INSTALL httpfs; LOAD httpfs;
ATTACH 'https://huggingface.co/datasets/Nason/ussc-database/resolve/main/ussc.duckdb' AS ussc (READ_ONLY);

SELECT fiscal_year, COUNT(*) AS defendants,
       ROUND(100.0 * COUNT(*) FILTER (WHERE prison_imposed) / COUNT(*) FILTER (WHERE prison_imposed IS NOT NULL), 1) AS pct_prison_imposed,
       ROUND(AVG(prison_months) FILTER (WHERE term_type = 'months'), 1) AS mean_months_when_term_stated,
       COUNT(*) FILTER (WHERE term_type = 'life') AS life
FROM ussc.v_sentence_terms GROUP BY 1 ORDER BY 1;
-- TOTPRISN alone is neither averageable (9992/9996/9997/9998 are codes) nor a prison
-- indicator (0 = no prison OR under one month); the view separates both.

Or with the datapond packages: pip install datapond / pak::pak("datapond-db/datapond-r").

Build pipeline, the USSC codebook and caveats: https://github.com/ian-nason/ussc-database Source: https://www.ussc.gov/research/datafiles/commission-datafiles (public domain).

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