I have the below dataframe:
df = pd.DataFrame({'a': [2.85,3.11,3.3,3.275,np.NaN,4.21], 'b': [3.65,3.825,3.475,np.NaN,4.10,2.73], 'c': [4.3,3.08,np.NaN,2.40, 3.33, 2.48]}, index=pd.date_range('2019-01-01', periods=6, freq='M')) This gives the dataframe as below: a b c 2019-01-31 2.850 3.650 4.30 2019-02-28 3.110 3.825 3.08 2019-03-31 3.300 3.475 NaN 2019-04-30 3.275 NaN 2.40 2019-05-31 NaN 4.100 3.33 2019-06-30 4.210 2.730 2.48 Expected: a b c 2019-01-31 2.850 3.650 4.30 2019-02-28 3.110 3.825 3.08 2019-03-31 3.300 3.475 **3.69** 2019-04-30 3.275 **3.650** 2.40 2019-05-31 **3.220** 4.100 3.33 2019-06-30 4.210 2.730 2.48
I want to replace the NaN values with the 3 month rolling average. How should I got about this?
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Answer
If you take NaN
s as 0 into your means, can do:
df.fillna(0,inplace=True) df.rolling(3).mean()
This will give you:
a b c 2019-01-31 NaN NaN NaN 2019-02-28 NaN NaN NaN 2019-03-31 3.086667 3.650000 2.460000 2019-04-30 3.228333 2.433333 1.826667 2019-05-31 2.191667 2.525000 1.910000 2019-06-30 2.495000 2.276667 2.736667