pandas.core.resample.Resampler.count#

finalResampler.count()[source]#

Compute count of group, excluding missing values.

Returns:

Series or DataFrame

Count of values within each group.

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,np.nan],index=lst)>>>sera    1.0a    2.0b    NaNdtype: float64>>>ser.groupby(level=0).count()a    2b    0dtype: int64

For DataFrameGroupBy:

>>>data=[[1,np.nan,3],[1,np.nan,6],[7,8,9]]>>>df=pd.DataFrame(data,columns=["a","b","c"],...index=["cow","horse","bull"])>>>df        a         b     ccow     1       NaN     3horse   1       NaN     6bull    7       8.0     9>>>df.groupby("a").count()    b   ca1   0   27   1   1

For Resampler:

>>>ser=pd.Series([1,2,3,4],index=pd.DatetimeIndex(...['2023-01-01','2023-01-15','2023-02-01','2023-02-15']))>>>ser2023-01-01    12023-01-15    22023-02-01    32023-02-15    4dtype: int64>>>ser.resample('MS').count()2023-01-01    22023-02-01    2Freq: MS, dtype: int64