pandas.core.groupby.GroupBy.mean¶

GroupBy.mean(numeric_only=True)[source]¶

Compute mean of groups, excluding missing values.

Parameters

numeric_onlybool, 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
  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

pandas.core.groupby.GroupBy.max pandas.core.groupby.GroupBy.median