The pandas "groupby" method allows you to split a DataFrame into groups, apply a function to each group independently, and then combine the results back together. This is called the "split-apply-combine" pattern, and is a powerful tool for analyzing data across different categories. In this video, I'll explain when you should use a groupby and then demonstrate its flexibility using four different examples.

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== RESOURCES ==
GitHub repository for the series: https://github.com/justmarkham/pandas-videos
"groupby" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html
"agg" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.core.groupby.DataFrameGroupBy.agg.html
"plot" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.plot.html

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