Identifying Census Tracts with Python

This guide demonstrates how to use Python to find out which census tract contains a specific longitude and latitude coordinate by utilizing a GeoJSON database of polygons.

Prerequisites

Ensure you have the Shapely library installed, which is essential for geometric operations. You can install it using pip:

pip install shapely

Step-by-Step Implementation

  1. Load the GeoJSON Data: First, you need to load your GeoJSON file that contains the census tracts.
  2. Create a Point: Define the point using the longitude and latitude.
  3. Check for Containment: Iterate through the polygons in the GeoJSON to check if the point lies within any of them.

Example Code

Here’s a sample code snippet to achieve this:

import json
from shapely.geometry import shape, Point

# Load the GeoJSON file containing census tracts
with open('census_tracts.geojson') as f:
    geojson_data = json.load(f)

# Define the point using longitude and latitude
longitude = -122.7924463
latitude = 45.4519896
point = Point(longitude, latitude)

# Check each polygon to see if it contains the point
for feature in geojson_data['features']:
    polygon = shape(feature['geometry'])
    if polygon.contains(point):
        print('Found containing polygon:', feature['properties'])

Explanation

  • Loading GeoJSON: The code reads the GeoJSON file and loads it into a Python dictionary.
  • Creating a Point: A Point object is created using the specified longitude and latitude.
  • Polygon Containment Check: The code iterates through each feature in the GeoJSON, converting the geometry to a polygon and checking if it contains the point. If it does, it prints the properties of the containing polygon.

Conclusion

This method allows you to efficiently determine the census tract for any given coordinate using Python and GeoJSON data. Adjust the file path and coordinates as needed for your specific use case.