pyspark.pandas.groupby.GroupBy.mean¶
-
GroupBy.mean() → FrameLike[source]¶ Compute mean of groups, excluding missing values.
- Returns
- pyspark.pandas.Series or pyspark.pandas.DataFrame
Examples
>>> df = ps.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().sort_index() B C A 1 3.0 1.333333 2 4.0 1.500000