How to replace NaNs by preceding or next values in pandas DataFrame?

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You could use the fillna method on the DataFrame and specify the method as ffill (forward fill):

>>> df = pd.DataFrame([[1, 2, 3], [4, None, None], [None, None, 9]])
>>> df.fillna(method='ffill')
   0  1  2
0  1  2  3
1  4  2  3
2  4  2  9

This method…

propagate[s] last valid observation forward to next valid

To go the opposite way, there’s also a bfill method.

This method doesn’t modify the DataFrame inplace – you’ll need to rebind the returned DataFrame to a variable or else specify inplace=True:

df.fillna(method='ffill', inplace=True)

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