Severe-Weather Events - Data Science Guides (beta)
Welcome to the Severe-Weather Events' Data Science documentation. This content is provided as a resource for Data Science teams to help get them up and running quickly.
The current severe weather notebooks are at the beta stage and only provided for exploratory purposes. We are running a beta of forecasting with severe weather events over November to December 2021. PredictHQ will provide advice and support on how to use severe weather in your forecast. Please contact us if you’d like to participate in the beta.
We provide guides to using our API and data with common Data Science tools and libraries in Python. The articles include a link to Jupyter Notebooks that you can download and run. The guides include code samples and instructions for performing common tasks.
For background on the severe weather category please see also the Severe Weather category information documentation.
This How to Series consist of the following three notebooks, allows you to quickly extract the data (Part 1), explore the data (Part 2) and experiment with different aggregations (Part 3):
Part 1: Data Engineering shows you how to call the Events API to extract the data to a DataFrame.
Part 2: Data Exploration is a guide to exploring PredictHQ's Severe-Weather Events data for Data Science teams.
Part 3: Feature Engineering provides examples of how to aggregate and extract features from the data.