pythonpandasdataframenan

Pandas Dataframe fill with last value base on multiple condition

Suppose I have a DataFrame with some NaNs:

      result
0       1
1      NaN
2      NaN
3       1
4      NaN
5       2
6       2
7      NaN
8       1

What I need to do is replace every NaN with the last valid value, and i expecting result like this:

      result  Expected_Result
0       1            1
1      NaN           1
2      NaN           1
3       1            1
4      NaN           1
5       2            2
6       2            2
7      NaN           2
8       1            1

are its possible using np.whare to achieve this replacement value?

Solution

  • Use, pd.Dataframe.ffill means "forward-fill":

    df.ffill()

    Output:

       result
0     1.0
1     1.0
2     1.0
3     1.0
4     1.0
5     2.0
6     2.0
7     2.0
8     1.0

    When needed you can also use this as a function of a GroupBy objects to only forward-fill within a group. Documentation