Combine different columns into a new column in a dataframe using pandas-CodePudding

I have a sample dataframe of a very huge dataframe as given below.

import pandas as pd
import numpy as np

NaN = np.nan

data = {'Start_x':['Tom', NaN, NaN, NaN,NaN],
    'Start_y':[NaN, 'Nick', NaN, NaN, NaN],
    'Start_z':[NaN, NaN, 'Alison', NaN, NaN],
    'Start_a':[NaN, NaN, NaN, 'Mark',NaN],
    'Start_b':[NaN, NaN, NaN, NaN, 'Oliver'],
    'Sex': ['Male','Male','Female','Male','Male']}

df = pd.DataFrame(data)
df

I want the final result to look like the image given below. The 4 columns have to be merged to a single new column but the 'Sex' column should be as it is.

Any help is greatly appreciated. Thank you!

CodePudding user response：

One option could be to backfill Start columns by rows and then take the first column:

df['New_Column'] = df.filter(like='Start').bfill(axis=1).iloc[:, 0]

df
  Start_x Start_y Start_z Start_a Start_b     Sex New_Column
0     Tom     NaN     NaN     NaN     NaN    Male        Tom
1     NaN    Nick     NaN     NaN     NaN    Male       Nick
2     NaN     NaN  Alison     NaN     NaN  Female     Alison
3     NaN     NaN     NaN    Mark     NaN    Male       Mark
4     NaN     NaN     NaN     NaN  Oliver    Male     Oliver