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# pandas.api.typing.SeriesGroupBy.size

SeriesGroupBy.size()

  Compute group sizes.

  Returns the number of rows in each group. This is useful for understanding the distribution of data across groups.

  Returns:
    DataFrame or Series

      Number of rows in each group as a Series if as_index is True or a DataFrame if as_index is False.

  See also

  `Series.size`

    Apply function size to a Series.

  `DataFrame.size`

    Apply function size to each row or column of a DataFrame.

  Examples

  For SeriesGroupBy:

      >>> lst = ["a", "a", "b"]
      >>> ser = pd.Series([1, 2, 3], index=lst)
      >>> ser
      a     1
      a     2
      b     3
      dtype: int64
      >>> ser.groupby(level=0).size()
      a    2
      b    1
      dtype: int64

      >>> data = [[1, 2, 3], [1, 5, 6], [7, 8, 9]]
      >>> df = pd.DataFrame(
      ...     data, columns=["a", "b", "c"], index=["owl", "toucan", "eagle"]
      ... )
      >>> df
              a  b  c
      owl     1  2  3
      toucan  1  5  6
      eagle   7  8  9
      >>> df.groupby("a").size()
      a
      1    2
      7    1
      dtype: int64

  For Resampler:

      >>> ser = pd.Series(
      ...     [1, 2, 3],
      ...     index=pd.DatetimeIndex(["2023-01-01", "2023-01-15", "2023-02-01"]),
      ... )
      >>> ser
      2023-01-01    1
      2023-01-15    2
      2023-02-01    3
      dtype: int64
      >>> ser.resample("MS").size()
      2023-01-01    2
      2023-02-01    1
      Freq: MS, dtype: int64