data.gov.in API — Advanced Guide

Query India's open data portal programmatically — fetch any of 500,000+ datasets using Python.

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Provider

National Informatics Centre (NIC) / MeitY

API Base URL

https://api.data.gov.in/resource/

Access Level

🟡 Free API Key (register at data.gov.in)

Rate Limit

1,000 requests/day (free tier)

Response Format

JSON, XML, CSV

Docs

data.gov.in/help/api

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Getting Your API Key

1. Go to data.gov.in
2. Click "Sign In" → Register with email
3. After login: Go to "My Account" → "API Access"
4. Click "Generate API Key"
5. Copy the key — you'll use it in every API request

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API Endpoint Structure

Every dataset on data.gov.in has a Resource ID (UUID). The API call structure is:

https://api.data.gov.in/resource/{resource_id}?api-key={your_key}&format=json&limit=100

Key parameters:

Parameter	Description	Example
api-key	Your API key	abc123xyz
format	Response format	json, xml, csv
limit	Records per page	100 (max 500)
offset	Skip first N records	100 (for pagination)
filters[column]	Filter by column value	filters[State]=Maharashtra
fields	Select specific columns	fields=State,District,Total

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Python Wrapper for data.gov.in API

import requests
import pandas as pd
from time import sleep

class DataGovIn:
    """Simple wrapper for the data.gov.in API."""

    BASE_URL = "https://api.data.gov.in/resource/{resource_id}"

    def __init__(self, api_key: str):
        self.api_key = api_key

    def fetch(self, resource_id: str, filters: dict = None,
              fields: list = None, limit: int = 100) -> pd.DataFrame:
        """Fetch a dataset and return as DataFrame."""
        url = self.BASE_URL.format(resource_id=resource_id)

        params = {
            "api-key": self.api_key,
            "format": "json",
            "limit": limit,
            "offset": 0
        }

        if filters:
            for col, val in filters.items():
                params[f"filters[{col}]"] = val

        if fields:
            params["fields"] = ",".join(fields)

        all_records = []

        while True:
            resp = requests.get(url, params=params, timeout=30)

            if resp.status_code != 200:
                print(f"Error {resp.status_code}: {resp.text[:200]}")
                break

            data = resp.json()
            records = data.get("records", [])
            all_records.extend(records)

            total = int(data.get("total", 0))
            offset = params["offset"] + limit

            print(f"  Fetched {len(all_records)}/{total} records...")

            if offset >= total or not records:
                break

            params["offset"] = offset
            sleep(0.5)  # Be polite to the server

        return pd.DataFrame(all_records)

    def search(self, query: str) -> list:
        """Search for datasets by keyword."""
        resp = requests.get(
            "https://data.gov.in/api/3/action/package_search",
            params={"q": query, "rows": 10}
        )
        results = resp.json().get("result", {}).get("results", [])
        return [(r.get("title"), r.get("id")) for r in results]


# ─── Usage Example ────────────────────────────────────────────────────────────

api = DataGovIn(api_key="YOUR_API_KEY_HERE")

# Example: Download MGNREGA data for Maharashtra
# Resource ID found by searching on data.gov.in
MGNREGA_RESOURCE_ID = "628f3a50-5b70-4b55-88c0-d4b6f618d855"

print("Downloading MGNREGA data for Maharashtra...")
mgnrega_mh = api.fetch(
    resource_id=MGNREGA_RESOURCE_ID,
    filters={"State": "MAHARASHTRA"},
    limit=500
)

print(f"\nDownloaded {len(mgnrega_mh)} records")
print(mgnrega_mh.head())

# Save to CSV
mgnrega_mh.to_csv("mgnrega_maharashtra.csv", index=False)
print("Saved to mgnrega_maharashtra.csv")

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Finding Resource IDs

To find the Resource ID for any dataset:

1. Go to data.gov.in → Search for your dataset
2. Click on the dataset → Scroll to "API" section
3. The Resource ID is in the URL or the API panel

Or search via the API:

# Search data.gov.in catalogue
results = api.search("MGNREGA district Maharashtra")
for title, rid in results:
    print(f"{rid}  →  {title}")

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✏️ Practice Exercise

Exercise 6.4 — Auto-download PMGSY Data for Your State

Goal: Write a Python script to download and save PMGSY road connectivity data.

1. Go to data.gov.in → Search: "PMGSY habitation" → Find a suitable dataset
2. Note the Resource ID from the API section
3. Use the DataGovIn wrapper above:

api = DataGovIn(api_key="YOUR_KEY")

pmgsy_data = api.fetch(
    resource_id="YOUR_PMGSY_RESOURCE_ID",
    filters={"State_Name": "MAHARASHTRA"},  # Adjust column name
    limit=500
)

print(f"Total records: {len(pmgsy_data)}")
print(f"Columns: {list(pmgsy_data.columns)}")

# Count connected vs unconnected
status_counts = pmgsy_data['Status'].value_counts()
print("\nConnectivity Status:")
print(status_counts)

pmgsy_data.to_csv("pmgsy_my_state.csv", index=False)

• How many habitations are in your state's PMGSY database?
• What % are connected?
• Which district has the most unconnected habitations?

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