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 pd
df = 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
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