The National Weather Service API provides free forecast data that Python scripts can retrieve and refresh for stakeholder analyses. A typical workflow requests a location’s forecast, checks the response, converts JSON into a pandas DataFrame, selects useful fields, and reshapes the results for reporting. section 10.1.1
A practical forecast-data workflow includes:
- Review the API documentation and request a location-specific forecast with Python’s requests library. section 10.1.1
- Interpret a successful response, save it as JSON, and inspect nested keys such as properties and periods. section 10.1.1
- Load forecast periods into pandas, extract dates and fields, clean wind-speed text, and aggregate temperatures by day. section 10.1.1
import requests import json #1 url = "https://api.weather.gov/gridpoints/OKX/34,36/forecast" #2 response = requests.get(url) #3 print(response) #4
The request pattern uses a weather.gov gridpoint forecast endpoint and prints the HTTP response before parsing its contents. section 10.1.1
