how to create a row for each corresponding column

Question

I have a data frame which formatted like this:

-	Name	0	1	2	3
0	John	object 1	object 2	Object 3	object 4
1	Smith	object 1	object 2	Object 3	object 4
2	Jack	object 1	object 2	Object 3	object 4

and I want to transform it to the following:

-	Name	0
0	John	object1
1	John	object2
2	John	object3
3	John	object4
4	Smith	object1
5	Smith	object2
6	Smith	object3
7	Smith	object4
8	Jack	object1
9	Jack	object2
10	Jack	object3
11	Jack	object4

Answer 1

You could try:

import pandas as pd
import numpy as np

df = (pd.melt(df, id_vars=['Name'], value_vars=df.columns[1:])
 .drop(columns=['variable'])
 .sort_values(by='Name')
 .pipe(lambda g: g.set_axis(np.arange(0, len(g.index)), axis=0)))

df

     Name     value
0    Jack  object 1
1    Jack  object 2
2    Jack  Object 3
3    Jack  object 4
4    John  object 1
5    John  object 2
6    John  Object 3
7    John  object 4
8   Smith  object 1
9   Smith  object 2
10  Smith  Object 3
11  Smith  object 4