forward fill specific columns in pandas dataframe

Question

If I have a dataframe with multiple columns [\'x\', \'y\', \'z\'], how do I forward fill only one column \'x\'? Or a group of columns [\'x\',

Answer 1

for col in ['X', 'Y']:
    df[col] = df[col].ffill()

Answer 2

tl;dr:

cols = ['X', 'Y']
df.loc[:,cols] = df.loc[:,cols].ffill()

And I have also added a self containing example:

>>> import pandas as pd
>>> import numpy as np
>>> 
>>> ## create dataframe
... ts1 = [0, 1, np.nan, np.nan, np.nan, np.nan]
>>> ts2 = [0, 2, np.nan, 3, np.nan, np.nan]
>>> d =  {'X': ts1, 'Y': ts2, 'Z': ts2}
>>> df = pd.DataFrame(data=d)
>>> print(df.head())
    X   Y   Z
0   0   0   0
1   1   2   2
2 NaN NaN NaN
3 NaN   3   3
4 NaN NaN NaN
>>> 
>>> ## apply forward fill
... cols = ['X', 'Y']
>>> df.loc[:,cols] = df.loc[:,cols].ffill()
>>> print(df.head())
   X  Y   Z
0  0  0   0
1  1  2   2
2  1  2 NaN
3  1  3   3
4  1  3 NaN

Answer 3

I used below code, Here for X and Y method can be different also instead of ffill().

 df1 = df.fillna({
        'X' : df['X'].ffill(),
        'Y' : df['Y'].ffill(),
    })

Answer 4

Two columns can be ffill() simultaneously as given below:

df1 = df[['X','Y']].ffill()