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# pandas.core.groupby.DataFrameGroupBy.mean

DataFrameGroupBy.mean(numeric_only=False, engine=None, engine_kwargs=None)

  Compute mean of groups, excluding missing values.

  Parameters:
    numeric_only bool, default False

      Include only float, int, boolean columns.

      Changed in version 2.0.0: numeric_only no longer accepts `None` and defaults to `False`.

    engine str, default None

      - `'cython'` : Runs the operation through C-extensions from cython.

      - `'numba'` : Runs the operation through JIT compiled code from numba.

      - `None` : Defaults to `'cython'` or globally setting `compute.use_numba`

      Added in version 1.4.0.

    engine_kwargs dict, default None

      - For `'cython'` engine, there are no accepted `engine_kwargs`

      - For `'numba'` engine, the engine can accept `nopython`, `nogil` and `parallel` dictionary keys. The values must either be `True` or `False`. The default `engine_kwargs` for the `'numba'` engine is `{{'nopython': True, 'nogil': False, 'parallel': False}}`

      Added in version 1.4.0.

  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