How to fill nan values with rolling mean in pandas
This should work:
input_data_frame[var_list]= input_data_frame[var_list].fillna(pd.rolling_mean(input_data_frame[var_list], 6, min_periods=1))Note that the window is 6 because it includes the value of NaN itself (which is not counted in the average). Also the other NaN values are not used for the averages, so if less that 5 values are found in the window, the average is calculated on the actual values.
Example:
df = {'a': [1, 1,2,3,4,5, np.nan, 1, 1, 2, 3, 4, 5, np.nan] }df = pd.DataFrame(data=df)print df a0 1.01 1.02 2.03 3.04 4.05 5.06 NaN7 1.08 1.09 2.010 3.011 4.012 5.013 NaNOutput:
a0 1.01 1.02 2.03 3.04 4.05 5.06 3.07 1.08 1.09 2.010 3.011 4.012 5.013 3.0