fill NaN based on other columns value

Question

I have a data frame like this :

NAME    YEAR    WFR MEAN
0   A   2017    20  NaN
1   B   2009    50  65.0
2   B   2011    80  65.0
3   B   2017    60  65.0
4   B   2018    90  NaN
5   C   2010    10  10.0
6   C   2018    30  10.0
7   D   2014    40  47.5
8   D   2015    55  47.5
9   D   2016    45  47.5

I want to fill the NaN with the value of WFR: if the MEAN was NaN then the MEAN is equal to the value of WFR in that year . any idea ? Thanks

score 1 · Answer 1 · answered Nov 07 '21 at 15:38

>>> mask = df.MEAN.isna()
>>> df.loc[mask, "MEAN"] = df.loc[mask, "WFR"]
>>> df

  NAME  YEAR  WFR  MEAN
0    A  2017   20  20.0
1    B  2009   50  65.0
2    B  2011   80  65.0
3    B  2017   60  65.0
4    B  2018   90  90.0
5    C  2010   10  10.0
6    C  2018   30  10.0
7    D  2014   40  47.5
8    D  2015   55  47.5
9    D  2016   45  47.5

score 1 · Accepted Answer · answered Nov 07 '21 at 15:39

1

Try this:

df['MEAN'] = df['MEAN'].fillna(df['WFR'])

answered Nov 07 '21 at 15:39

fill NaN based on other columns value

2 Answers2