Data analysis in Python with pandas - When should I use a "groupby" in pandas?

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. SUBSCRIBE to learn data science with Python: https://www.youtube.com/dataschool?sub_confirmation=1 JOIN the "Data School Insiders" community and receive exclusive rewards: https://www.patreon.com/dataschool == 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 == LET'S CONNECT! == Newsletter: https://www.dataschool.io/subscribe/ Twitter: https://twitter.com/justmarkham Facebook: https://www.facebook.com/DataScienceSchool/ LinkedIn: https://www.linkedin.com/in/justmarkham/