I am trying to create a new column based on both columns. Say I want to create a new column z, and it should be the value of y when it is not missing and be the value of x when y is indeed missing. So in this case, I expect z to be [1, 8, 10, 8]
.
x y
0 1 NaN
1 2 8
2 4 10
3 8 NaN
The new column 'z'
get its values from column 'y'
using df['z'] = df['y']
. This brings over the missing values so fill them in using fillna
using column 'x'
. Chain these two actions:
>>> df['z'] = df['y'].fillna(df['x'])
>>> df
x y z
0 1 NaN 1
1 2 8 8
2 4 10 10
3 8 NaN 8