# Severe Weather Events Notebooks

For background on the severe weather category please see also the [Severe Weather category information documentation](https://docs.predicthq.com/predicthq-data/event-categories/unscheduled-events#severe-weather).

This How to Series consist of the following three Jupyter  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**](https://github.com/predicthq/phq-data-science-docs/blob/master/severe-weather-events/part_1_data_engineering.ipynb) shows you how to call the Events API to extract Severe-Weather events to a Pandas DataFrame.
* [**Part 2: Data Exploration**](https://github.com/predicthq/phq-data-science-docs/blob/master/severe-weather-events/part_2_data_exploration.ipynb) is a guide to exploring PredictHQ's Severe-Weather events for Data Science teams.
* [**Part 3: Feature Engineering**](https://github.com/predicthq/phq-data-science-docs/blob/master/severe-weather-events/part_3_feature_engineering.ipynb) provides examples of how to aggregate and extract features from the Severe-Weather events.

{% embed url="<https://www.youtube.com/watch?v=Hp_F_tTMzc8>" %}
Forecasting with Severe Weather - Part 1
{% endembed %}

{% embed url="<https://www.youtube.com/watch?v=1h140czy4so>" %}
Forecasting with Severe Weather - Part 2
{% endembed %}