fedcomp-index-data 2026.4.0

Pre-classified federal contractor datasets with FedComp Index Posture Class assignments via two-axis classification (volume x frequency). Updated monthly.

FedComp Index Data

Pre-classified federal contractor datasets bundled for Python. Each contractor has a Posture Class (1-4) assigned by two-axis classification (base contract dollars x base contract count) from five years of USASpending award data.

Updated monthly with fresh data from the FedComp Index pipeline.

Install

pip install fedcomp-index-data

Usage

from fedcomp_index_data import load_state, lookup

# Load all classified contractors for a state
contractors = load_state("NV")
print(f"{len(contractors)} contractors classified")

# Filter by posture class
class_1 = [c for c in contractors if c["posture_class"] == "Class 1"]
print(f"{len(class_1)} Class 1 contractors")

# Look up a specific contractor by UEI
c = lookup("CGAKREGGN9J3")
print(c["legal_name"])      # FLEET VEHICLE SOURCE INC
print(c["posture_class"])   # Class 1

Available states

State	Contractors	Updated
Nevada (NV)	348	March 2026

More states are added as the FedComp Index expands coverage.

Data fields

Field	Description
rank	Rank within the state (by base contract dollars)
legal_name	Registered legal name from SAM.gov
uei	Unique Entity Identifier
cage	CAGE code
posture_class	Posture Class: 1, 2, 3, or 4 (two-axis classification)
base_dollars_5yr	Base contract dollars over trailing 5-year window
base_contract_count	Number of distinct base contracts
award_count	Total award count (including delivery/task orders)
active_contracts	Currently active contracts
last_award_date	Date of most recent award (YYYY-MM)
primary_naics	Primary NAICS code
top_agency	Most frequent awarding agency
city	Registered city
certifications	SBA certifications (pipe-separated)
state	State of registration
scored_date	Year-month this classification was computed

Classification methodology (v1.1)

Two axes, no composite score, no weighted sum:

Axis	Threshold	What it measures
Base contract dollars (5yr)	$5M	Volume of competitively won work
Base contract count (5yr)	3	Frequency of distinct wins

Posture Class	Volume	Frequency	Profile
Class 1	$5M+	3+ contracts	Systematic winner
Class 2	$5M+	<3 contracts	Concentrated risk
Class 3	<$5M	3+ contracts	Growth pipeline
Class 4	<$5M	<3 contracts	Entry level

Full methodology: fedcompindex.org/methodology

Related packages

• fedcomp-index-scoring - classification engine
• fedcomp-index - meta-package

Data sources

• USASpending.gov - award history
• SAM.gov - entity registration
• SBA.gov - certification verification

Also available on npm

npm install fedcomp-index-data

• fedcomp-index - meta-package
• fedcomp-index-scoring - classification engine
• fedcomp-index-data - pre-classified datasets

Links

• Website: https://fedcompindex.org/
• Nevada Rankings: https://fedcompindex.org/nv/
• Methodology: https://fedcompindex.org/methodology/
• Tabularium: https://fedcompindex.org/tabularium/
• FAQ: https://fedcompindex.org/faq/
• Source: https://github.com/fedcompindex/FedCompIndex
• PyPI: https://pypi.org/project/fedcomp-index/
• PyPI (Scoring): https://pypi.org/project/fedcomp-index-scoring/
• PyPI (Data): https://pypi.org/project/fedcomp-index-data/
• HuggingFace: https://huggingface.co/datasets/npetro6/nevada-federal-contractors
• Kaggle: https://www.kaggle.com/datasets/npetro6/nevada-federal-contractors-fedcomp-index

License

MIT