How to replace NaNs by preceding values in pandas DataFrame?

Question

Suppose I have a DataFrame with some NaNs:

>>> import pandas as pd
>>> df = pd.DataFrame([[1, 2, 3], [4, None, None], [None, N         


        

Answer 1

Only one column version

• Fill NAN with last valid value

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

• Fill NAN with next valid value

df[column_name].fillna(method='backfill', inplace=True)