# dask.dataframe.api.GroupBy.mean

#### GroupBy.mean(numeric_only=False, split_out=None, \*\*kwargs)

Compute mean of groups, excluding missing values.

This docstring was copied from pandas.core.groupby.groupby.GroupBy.mean.

Some inconsistencies with the Dask version may exist.

* **Parameters:**
  **numeric_only**
  : Include only float, int, boolean columns.
    <br/>
    #### Versionchanged
    Changed in version 2.0.0: numeric_only no longer accepts `None` and defaults to `False`.

  **skipna**
  : Exclude NA/null values. If an entire group is NA, the result will be NA.

  **engine**
  : * `'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`

  **engine_kwargs**
  : * 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}`
* **Returns:**
  pandas.Series or pandas.DataFrame
  : Mean of values within each group. Same object type as the caller.

#### SEE ALSO
`Series.mean`
: Apply function mean to a Series.

`DataFrame.mean`
: Apply function mean to each row or column of a DataFrame.

### Examples

```pycon
>>> 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.

```pycon
>>> 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.

```pycon
>>> 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.

```pycon
>>> df.groupby("A")["B"].mean()
A
1    3.0
2    4.0
Name: B, dtype: float64
```

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