How to replace NaN values with 0 in index dataframe

Question

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How do I replace the NaN values to 0 while keeping it in this index form?

Anonymous · Answer 1 · 2019-01-23T07:15:26.590

0

You can process the original index as a Series first and then re-assign the index:

import pandas as pd
import numpy as np
df = pd.DataFrame({'Column1': [1, 2, 3, 4], 'Column2': [5, 6, 7, 8], 
'Column3': [8, 9, 10, 11]}, index=['a', 'b', np.nan, np.nan])
df.index = pd.Series(df.index).replace(np.nan, 0)
print df

Output:

          Column1  Column2  Column3
a           1         5        8
b           2         6        9
0           3         7        10
0           4         8        11

edited Jan 23 '19 at 07:15

answered Jan 23 '19 at 05:18

Anonymous

659
6
16

This does not fill na in the index. Please update your code. – Joe Patten Jan 23 '19 at 05:24
@JoePatten I have updated the code. – Anonymous Jan 24 '19 at 06:42

How to replace NaN values with 0 in index dataframe

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