Advanced Use of groupby(), aggregate, filter, transform, apply - Beginner Python Pandas Tutorial #5

This is beginner Python Pandas tutorial #5 and in this video, we’ll be diving into advanced use of groupby() method in pandas python. We’ll be covering the aggregate(), filter(), transform(), and apply() methods and showing a few interactive examples with each method. These methods are applied in conjunction with a groupby() on a pandas dataframe.

Documentation can be found here:
Pandas groupby(): https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.groupby.html
Pandas aggregate(): https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.aggregate.html
Pandas transform():
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.transform.html
Pandas apply():
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html
Pandas filter():
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.filter.html

Let me know if you have any questions and please offer feedback on how I can improve to help you better.

If you enjoyed this video, please throw in a like and subscribe to my channel. I’ll be posting a lot more videos on data science concepts that cover all things python and SQL.

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Follow along interactively and execute code with me as I walk through the concepts!

Python notebook used in the video: https://bit.ly/3gvHA6X

Datasets can be found here: https://bit.ly/3gsZdUS

After watching the video, test yourself with our python exercises: https://bit.ly/36AILxk

Python exercises with solutions: https://bit.ly/36v7p2a

Here’s help on how to run a python notebook using Google Colabs: https://bit.ly/2YXKR8o

Much of the content was adapted from the book and GitHub of Jake VanderPlas’s Python Data Science Handbook: https://jakevdp.github.io/PythonDataScienceHandbook/
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