pandas.core.groupby.GroupBy.mean
- GroupBy.mean(numeric_only=NoDefault.no_default)[source]
-
Compute mean of groups, excluding missing values.
- Parameters
-
- numeric_only:bool, default True
-
Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data.
- Returns
-
- pandas.Series or pandas.DataFrame
See also
Series.groupby
-
Apply a function groupby to a Series.
DataFrame.groupby
-
Apply a function groupby to each row or column of a DataFrame.
Examples
>>> df = pd.DataFrame({'A': [1, 1, 2, 1, 2], ... 'B': [np.nan, 2, 3, 4, 5], ... 'C': [1, 2, 1, 1, 2]}, columns=['A', 'B', 'C'])
Groupby one column and return the mean of the remaining columns in each group.
>>> df.groupby('A').mean() B C A 1 3.0 1.333333 2 4.0 1.500000
Groupby two columns and return the mean of the remaining column.
>>> df.groupby(['A', 'B']).mean() C A B 1 2.0 2.0 4.0 1.0 2 3.0 1.0 5.0 2.0
Groupby one column and return the mean of only particular column in the group.
>>> df.groupby('A')['B'].mean() A 1 3.0 2 4.0 Name: B, dtype: float64
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https://pandas.pydata.org/pandas-docs/version/1.3.4/reference/api/pandas.core.groupby.GroupBy.mean.html