pandas.core.groupby.GroupBy.mean

GroupBy.mean(*args, **kwargs)

Compute mean of groups, excluding missing values.

Returns:

pandas.Series or pandas.DataFrame

See also

pandas.Series., pandas.DataFrame., pandas.Panel.

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
  4.0  1
2 3.0  1
  5.0  2

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