pandas.core.window.Rolling.mean

Calculate the rolling mean of the values.

*args Under Review. **kwargs Under Review. :return: Series or DataFrame

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

Limitations

DataFrame/Series elements cannot be max/min float/integer. Otherwise SDC and Pandas results are different.

Examples

Calculate the rolling mean of the values.

import pandas as pd
from numba import njit


@njit
def series_rolling_mean():
    series = pd.Series([4, 3, 5, 2, 6])  # Series of 4, 3, 5, 2, 6
    out_series = series.rolling(3).mean()

    return out_series  # Expect series of NaN, NaN, 4.000000, 3.333333, 4.333333


print(series_rolling_mean())

$ python ./series/rolling/series_rolling_mean.py
0         NaN
1         NaN
2    4.000000
3    3.333333
4    4.333333
dtype: float64

Calculate the rolling mean of the values.

import pandas as pd
from numba import njit


@njit
def df_rolling_mean():
    df = pd.DataFrame({'A': [4, 3, 5, 2, 6], 'B': [-4, -3, -5, -2, -6]})
    out_df = df.rolling(3).mean()

    # Expect DataFrame of
    # {'A': [NaN, NaN, 4.000000, 3.333333, 4.333333],
    #  'B': [NaN, NaN, -4.000000, -3.333333, -4.333333]}
    return out_df


print(df_rolling_mean())

$ python ./dataframe/rolling/dataframe_rolling_mean.py
          A         B
0       NaN       NaN
1       NaN       NaN
2  4.000000 -4.000000
3  3.333333 -3.333333
4  4.333333 -4.333333

See also

Series.rolling

Calling object with a Series.

DataFrame.rolling

Calling object with a DataFrame.

Series.mean

Similar method for Series.

DataFrame.mean

Similar method for DataFrame.