pandas.core.resample.Resampler.size#

final Resampler.size()[source]#

Compute group sizes.

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.groupby: Apply a function groupby to a Series.
DataFrame.groupby: Apply a function groupby 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