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Government Contracts Dataset

Track federal government contract awards sourced from USAspending.gov and mapped to public company tickers. See which companies win government contracts, the awarding agencies, contract values, industry classifications, and contract periods.

What’s Included

Section titled “What’s Included”

The Government Contracts dataset provides:

  • Award Details: Award ID, amount, type, and contract award type
  • Agency Information: Awarding agency and sub-agency
  • Recipient Data: Recipient company name mapped to stock ticker
  • Contract Period: Start and end dates for each award
  • Industry Classification: NAICS codes and descriptions
  • Contract Description: Plain-text description of the contract scope

Coverage

Section titled “Coverage”
Source Description Update Frequency
USAspending.gov Federal contract awards mapped to stock tickers Daily

Government contracts data has 5+ years of historical awards available for backtesting.

FinBrain Terminal

Section titled “FinBrain Terminal”

Browse government contracts for any ticker directly in the FinBrain Terminal — with summary stats, filtering, and contract details at a glance.

LMT Government Contracts in FinBrain Terminal
Government contracts for Lockheed Martin (LMT) in the FinBrain Terminal

Use the Government Contracts screener to scan recent contract awards across all tickers, with filtering by company, agency, industry, and award amount.

Government Contracts Screener
Government Contracts screener showing recent federal contract awards

Quick Start

Section titled “Quick Start”
from finbrain import FinBrainClient


fb = FinBrainClient(api_key="YOUR_API_KEY")


df = fb.government_contracts.ticker("LMT", as_dataframe=True)
print(df)

For complete code examples in Python, JavaScript, C++, Rust, and cURL, see the API Reference.

Key Fields

Section titled “Key Fields”
Field Description Example
awardId Unique contract award identifier CONT_AWD_0001
awardAmount Total award value in USD 50000000
awardType Type of award Contract
awardingAgency Federal agency issuing the contract Department of Defense
awardingSubAgency Sub-agency within the awarding agency Department of the Army
recipientName Company receiving the contract Lockheed Martin Corporation
startDate Contract start date (YYYY-MM-DD) 2025-06-01
endDate Contract end date (YYYY-MM-DD) 2026-06-01
description Plain-text description of the contract Aircraft maintenance services
naicsCode NAICS industry classification code 336411
naicsDescription Human-readable NAICS description Aircraft Manufacturing
contractAwardType Specific contract award mechanism Definitive Contract

Use Cases

Section titled “Use Cases”

Top Contract Recipients

Section titled “Top Contract Recipients”

Scan defense tickers to find companies with the highest total contract value:

from finbrain import FinBrainClient


fb = FinBrainClient(api_key="YOUR_API_KEY")


def scan_contract_value(symbols):
    """Find companies with the highest government contract value"""
    results = []


    for symbol in symbols:
        try:
            df = fb.government_contracts.ticker(symbol, as_dataframe=True)


            total_value = df["awardAmount"].sum()
            results.append({
                "symbol": symbol,
                "contracts": len(df),
                "total_value": total_value
            })
        except Exception:
            continue


    return sorted(results, key=lambda x: x["total_value"], reverse=True)


defense_symbols = ["LMT", "RTX", "GD", "NOC", "BA"]
recipients = scan_contract_value(defense_symbols)


for r in recipients:
    print(f"{r['symbol']}: {r['contracts']} contracts, ${r['total_value']:,.0f} total value")

Agency Breakdown

Section titled “Agency Breakdown”

Analyze which federal agencies award contracts to a given company:

from finbrain import FinBrainClient


fb = FinBrainClient(api_key="YOUR_API_KEY")


def agency_breakdown(symbol):
    """Break down contracts by awarding agency"""
    df = fb.government_contracts.ticker(symbol, as_dataframe=True)


    by_agency = df.groupby("awardingAgency").agg(
        contracts=("awardAmount", "count"),
        total_value=("awardAmount", "sum")
    ).sort_values("total_value", ascending=False)


    return by_agency


agencies = agency_breakdown("LMT")
for agency, row in agencies.iterrows():
    print(f"{agency}: {row['contracts']} contracts, ${row['total_value']:,.0f}")

Contract Size Analysis

Section titled “Contract Size Analysis”

Categorize contracts by size to understand the award distribution:

import pandas as pd
from finbrain import FinBrainClient


fb = FinBrainClient(api_key="YOUR_API_KEY")


def contract_size_distribution(symbol):
    """Categorize contracts by size buckets"""
    df = fb.government_contracts.ticker(symbol, as_dataframe=True)


    bins = [0, 1_000_000, 10_000_000, 100_000_000, float("inf")]
    labels = ["Under $1M", "$1M–$10M", "$10M–$100M", "$100M+"]


    df["size_bucket"] = pd.cut(df["awardAmount"], bins=bins, labels=labels)


    distribution = df.groupby("size_bucket", observed=True).agg(
        contracts=("awardAmount", "count"),
        total_value=("awardAmount", "sum")
    )


    return distribution


dist = contract_size_distribution("RTX")
for bucket, row in dist.iterrows():
    print(f"{bucket}: {row['contracts']} contracts, ${row['total_value']:,.0f}")
Section titled “Related Resources”