pandas.core.window.Rolling.count

The rolling count of any non-NaN observations inside the window.

return

Series or DataFrame Returned object type is determined by the caller of the rolling calculation.

Examples

Count of any non-NaN observations inside the window.

import numpy as np
import pandas as pd
from numba import njit


@njit
def series_rolling_count():
    series = pd.Series([4, 3, 2, np.nan, 6])  # Series of 4, 3, 2, np.nan, 6
    out_series = series.rolling(3).count()

    return out_series  # Expect series of 1.0, 2.0, 3.0, 2.0, 2.0


print(series_rolling_count())

$ python ./series/rolling/series_rolling_count.py
0    1.0
1    2.0
2    3.0
3    2.0
4    2.0
dtype: float64

Count of any non-NaN observations inside the window.

import numpy as np
import pandas as pd
from numba import njit


@njit
def df_rolling_count():
    df = pd.DataFrame({'A': [4, 3, 2, np.nan, 6], 'B': [4, np.nan, 2, np.nan, 6]})
    out_df = df.rolling(3).count()

    # Expect DataFrame of
    # {'A': [1.0, 2.0, 3.0, 2.0, 2.0], 'B': [1.0, 1.0, 2.0, 1.0, 2.0]}
    return out_df


print(df_rolling_count())

$ python ./dataframe/rolling/dataframe_rolling_count.py
     A    B
0  1.0  1.0
1  2.0  1.0
2  3.0  2.0
3  2.0  1.0
4  2.0  2.0

See also

Series.rolling

Calling object with a Series.

DataFrame.rolling

Calling object with a DataFrame.

Series.count

Similar method for Series.

DataFrame.count

Similar method for DataFrame.