Transpose columns pandas dataframe

Question

I have a DF like this:

ID	Name	Mail	Phone1	Phone2	Mail1	Mail2	contact phone	contact mail
70	DASS ARGENTINA SRL	[email protected]	2664941642	2664941644	[email protected]	[email protected]	115456789	[email protected]
71	PEPSI	[email protected]	0456535365	7766554399	[email protected]	[email protected]	8864545332	[email protected]

ID	Name	LOCATOR
70	DASS ARGENTINA SRL	[email protected]
70	DASS ARGENTINA SRL	2664941642
70	DASS ARGENTINA SRL	2664941644
70	DASS ARGENTINA SRL	[email protected]
70	DASS ARGENTINA SRL	[email protected]
70	DASS ARGENTINA SRL	115456789
70	DASS ARGENTINA SRL	[email protected]
71	PEPSI	[email protected]
71	PEPSI	0456535365
71	PEPSI	7766554399
71	PEPSI	[email protected]
71	PEPSI	[email protected]
71	PEPSI	8864545332
71	PEPSI	[email protected]

Is it possible to do anythong like this? I´ve tried with transpose function but I´m not getting the output like the example above

Answer 1

use pd.melt to flatten the dataframe and then sort and remove the unwanted columns

df.drop(columns='ID').melt(id_vars='Name', value_name='Locator').sort_values('Name').drop(columns='variable')

                  Name  Locator
0   DASS ARGENTINA SRL  [email protected]
2   DASS ARGENTINA SRL  2664941642
4   DASS ARGENTINA SRL  2664941644
6   DASS ARGENTINA SRL  [email protected]
8   DASS ARGENTINA SRL  [email protected]
10  DASS ARGENTINA SRL  115456789
12  DASS ARGENTINA SRL  [email protected]
1   PEPSI               [email protected]
3   PEPSI               456535365
5   PEPSI               7766554399
7   PEPSI               [email protected]
9   PEPSI               [email protected]
11  PEPSI               8864545332
13  PEPSI               [email protected]