here is my sample df:
x y
0 0 1.1
1 1 3.9
2 2 11.2
3 3 21.5
4 4 34.8
5 5 51.0
6 6 70.2
7 7 NaN
8 8 NaN
9 9 NaN
If I would like to replace the NaN values and ffill the last number (70.2 – in this case), I would simply apply:
df['y'].ffill(inplace=True)
However, what if I would like to apply a custom function instead of ffill() method: For instance, I need the NaN values of y column to be replaced with "2 * x^2". See the desired output df:
x y
0 0 1.1
1 1 3.9
2 2 11.2
3 3 21.5
4 4 34.8
5 5 51.0
6 6 70.2
7 7 98
8 8 128
9 9 162
Just to illustrate: 2 * 7^2 = 98 etc
I appreciate any help.
>Solution :
In your case do
df['y'] = df.y.fillna(df.x**2*2)
0 1.1
1 3.9
2 11.2
3 21.5
4 34.8
5 51.0
6 70.2
7 98.0
8 128.0
9 162.0
Name: y, dtype: float64