The geocoder.py script is designed to take an input CSV and generate a new CSV annotated with latitude, longitude and other metadata from the Stanford ArcGIS geocoding API.
To use it, you should ensure your input file has the following columns:
Address- the street addressCity- the Jurisdiction (e.g.Alameda)Region- aka the state postal code (e.g.CA)
Once you've updated your source data as above, you can attempt to geocode your original CSV by executing it with the path to the source data file.
The below assumes you're doing this work using our standard Datakit project workflow. We use a file containing a small set of housing data for Alameda for demonstration purposes.
Navigate to your Datakit project:
# Use the appropriate path for your machine and project
cd ~/code/my-project
# Install requests
pipenv install requests
# Activate the virtual environment
pipenv shell
Assuming you've saved geocoder.py in scripts/, you can run it as below:
cd scripts/
# Call the script with the path to the data file.
# Here we use an example data file that you can find in this code folder
python geocoder.py ~/code/my-project/data/alameda.csvThe script should create a new file in the same directory as the source data.
The new file will have a _geocoded.csv suffix. So in the above example, you should have a new file called ~/code/my-project/data/alameda_geocoded.csv.