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We've used the "inplace" parameter many times during this video series, but what exactly does it do, and when should you use it? In this video, I'll explain how "inplace" affects methods such as "drop" and "dropna", and why it is always False by default. 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 "drop" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.drop.html "dropna" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.dropna.html "set_index" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.set_index.html "fillna" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.fillna.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/
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