dask.dataframe.api.SeriesGroupBy.size

SeriesGroupBy.size(**kwargs)

Compute group sizes.

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

Some inconsistencies with the Dask version may exist.

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