I have a dataframe like this.

   Project 4    Project1    Project2    Project3
0   NaN         laptio          AB      NaN
1   NaN         windows         ten     NaN
0   one         NaN             NaN
1   two         NaN             NaN

I want to delete NaN values from Project 4 column

My desired output should be,

df,

   Project 4    Project1    Project2    Project3
0   one         laptio          AB      NaN
1   two         windows         ten     NaN
0                   NaN        NaN       NaN
1                NaN            NaN

If your data frame's index is just standard 0 to n ordered integers, you can pop the Project4 column to a series, drop the NaN values, reset the index, and then merge it back with the data frame.

import pandas a pddf = pd.DataFrame([[pd.np.nan, 1,2,3],[pd.np.nan, 4,5,6],['one',7,8,9],['two',10,11,12]], columns=['p4','p1','p2','p3'])s = df.pop('p4')
pd.concat([df, ps.dropna().reset_index(drop=True)], axis=1)# returns:p1  p2  p3   p4
0   1   2   3  one
1   4   5   6  two
2   7   8   9  NaN
3  10  11  12  NaN