pandas.core.resample.Resampler.median — pandas 2.2.3 documentation (original) (raw)

final Resampler.median(numeric_only=False, *args, **kwargs)[source]#

Compute median of groups, excluding missing values.

For multiple groupings, the result index will be a MultiIndex

Parameters:

numeric_onlybool, default False

Include only float, int, boolean columns.

Changed in version 2.0.0: numeric_only no longer accepts None and defaults to False.

Returns:

Series or DataFrame

Median of values within each group.

Examples

For SeriesGroupBy:

lst = ['a', 'a', 'a', 'b', 'b', 'b'] ser = pd.Series([7, 2, 8, 4, 3, 3], index=lst) ser a 7 a 2 a 8 b 4 b 3 b 3 dtype: int64 ser.groupby(level=0).median() a 7.0 b 3.0 dtype: float64

For DataFrameGroupBy:

data = {'a': [1, 3, 5, 7, 7, 8, 3], 'b': [1, 4, 8, 4, 4, 2, 1]} df = pd.DataFrame(data, index=['dog', 'dog', 'dog', ... 'mouse', 'mouse', 'mouse', 'mouse']) df a b dog 1 1 dog 3 4 dog 5 8 mouse 7 4 mouse 7 4 mouse 8 2 mouse 3 1 df.groupby(level=0).median() a b dog 3.0 4.0 mouse 7.0 3.0

For Resampler:

ser = pd.Series([1, 2, 3, 3, 4, 5], ... index=pd.DatetimeIndex(['2023-01-01', ... '2023-01-10', ... '2023-01-15', ... '2023-02-01', ... '2023-02-10', ... '2023-02-15'])) ser.resample('MS').median() 2023-01-01 2.0 2023-02-01 4.0 Freq: MS, dtype: float64