pandas.DataFrame.groupby — pandas 2.2.3 documentation
pandas.DataFrame.groupby# DataFrame.groupby(by=None, axis=<no_default>, level=None, as_index=True, sort=True, group_keys=True, observed=<no_default>, dropna=True)[source]# Group DataFrame using a mapper or by a Series of columns. A groupby operation involves some combination of splitting the object, applying a function, and combining the results. This can be used to group large amounts of data and
pandas.DataFrame.dropna — pandas 2.2.3 documentation
pandas.DataFrame.dropna# DataFrame.dropna(*, axis=0, how=<no_default>, thresh=<no_default>, subset=None, inplace=False, ignore_index=False)[source]# Remove missing values. See the User Guide for more on which values are considered missing, and how to work with missing data. Parameters: axis{0 or ‘index’, 1 or ‘columns’}, default 0Determine if rows or columns which contain missing values are remove
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pandas.DataFrame.set_index — pandas 2.2.3 documentation
pandas.DataFrame.rolling — pandas 2.2.3 documentation
pandas.DataFrame.resample — pandas 2.2.3 documentation
pandas.DataFrame.quantile — pandas 2.2.3 documentation
pandas.DataFrame.sort_index — pandas 2.2.3 documentation
pandas.DataFrame.reindex — pandas 2.2.3 documentation
pandas.DataFrame.to_csv — pandas 2.2.3 documentation
pandas.DataFrame.notnull — pandas 2.2.3 documentation
pandas.DataFrame.mean — pandas 2.2.3 documentation
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pandas.DataFrame.astype — pandas 2.2.3 documentation
pandas.DataFrame.reset_index — pandas 2.2.3 documentation
pandas.DataFrame.pivot_table — pandas 2.2.3 documentation
pandas.DataFrame.boxplot — pandas 2.2.3 documentation
pandas.DataFrame.info — pandas 2.2.3 documentation
pandas.DataFrame.shape — pandas 2.2.3 documentation
pandas.DataFrame.tail — pandas 2.2.3 documentation
DataFrame — pandas 2.2.3 documentation