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Data.gov hosts 300,000+ datasets from US federal agencies covering health, education, environment, agriculture, finance, and transportation. Used in data engineering for government analytics pipelines, public health research, geospatial analysis, and building civic data applications with Python.
Engineers use the data.gov CKAN API or direct CSV/API endpoint links to fetch federal datasets. Many datasets on data.gov have their own agency APIs; the portal provides discovery and metadata while data retrieval uses agency-specific endpoints.
Data.gov is a treasure trove for building AI applications in civic tech, public health, and environmental monitoring. Index federal datasets for RAG systems that can answer policy questions with authoritative government data, or train domain-specific AI models on government-curated labeled datasets.
# pip install requests pandas
import requests, pandas as pd
# Search data.gov CKAN API for datasets about air quality
resp = requests.get("https://catalog.data.gov/api/3/action/package_search",
params={"q": "air quality", "rows": 5})
datasets = resp.json()["result"]["results"]
for ds in datasets:
print(ds["title"])Official dataset source
More datasets used by Python data engineers.
The FEC provides access to campaign finance data, including information on political contributions, campaign expenditures, fundraising activities and financial disclosures filed by political candidates, parties and committees in the United States.
The US Federal Aviation Administration publishes datasets on aircraft registrations, pilot certifications, airport data, accident reports, and air traffic statistics. Used in data engineering for aviation analytics pipelines, safety analysis systems, and building aeronautical intelligence dashboards in Python.
Data.gov.uk provides datasets from UK central and local government covering crime, transport, planning, health, and environment. Used in data engineering for public sector analytics, policy research pipelines, geospatial visualisation, and building civic technology applications in Python.