'How to fill nan values with rolling mean in pandas

I have a dataframe which contains nan values at few places. I am trying to perform data cleaning in which I fill the nan values with mean of it's previous five instances. To do so, I have come up with the following.

input_data_frame[var_list].fillna(input_data_frame[var_list].rolling(5).mean(), inplace=True)

But, this is not working. It isn't filling the nan values. There is no change in the dataframe's null count before and after the above operation. Assuming I have a dataframe with just integer column, How can I fill NaN values with mean of the previous five instances? Thanks in advance.

Solution 1:^[1]

rolling_mean function has been modified in pandas. If you fill the entire dataset, you can use;

filled_dataset = dataset.fillna(dataset.rolling(6,min_periods=1).mean())

Solution 2:^[2]

you can simply use interpolate()

df = {'a': [1,5, np.nan, np.nan, np.nan, 2, 5, np.nan] }
df = pd.DataFrame(data=df)
print(df)


df['a'].interpolate()

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Source: Stack Overflow

Solution	Source
Solution 1	Caner Erden
Solution 2	Franz Eigner

'How to fill nan values with rolling mean in pandas

Solution 1:[1]

Solution 2:[2]

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