# Live TV Events Notebooks

These guides consist of the following three notebooks:

* [**Part 1: Data Engineering:**](https://github.com/predicthq/phq-data-science-docs/blob/master/live-tv-events/part_1_data_engineering.ipynb) shows you how you could call the Live TV Events Broadcast API to extract data to a DataFrame.
* [**Part 2: Data Exploration**](https://github.com/predicthq/phq-data-science-docs/blob/master/live-tv-events/part_2_data_exploration.ipynb) provides a guide to exploring PredictHQ's Live TV Events data for Data Science teams.
* [**Part 3: Feature Engineering**](https://github.com/predicthq/phq-data-science-docs/blob/master/live-tv-events/part_3_feature_engineering.ipynb) provides examples of how to aggregate and extract features from the data.

{% embed url="<https://www.youtube.com/watch?v=YfE7tfuFGS0>" %}
Walk through the TV Events Jupyter Notebook with Data Scientist Andrew Walker - Part 1
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{% embed url="<https://www.youtube.com/watch?v=pv1oPK1l4Ok>" %}
Walk through the TV Events Jupyter Notebook with Data Scientist Andrew Walker - Part 2
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