Is there a way to groupby multiple columns under a single column in pandas?

Question

I have a table like this ---

AREA	COL1	COL2	COL3
Dhaka	[1,2,3]	[2,3]	[4,5,6]
Sylhet	[10,11]	[7,9,10]	[10,13,7]

I want this table in this shape--

Area	total_num
Dhaka	1
	2
	3
	4
	5
	6
Sylhet	10
	11
	7
	9
	13

how can I do it in pandas?

Answer 1

If necessary convert values to lists:

import ast

df.iloc[:, 1:] = df.iloc[:, 1:].applymap(ast.literal_eval)

And then reshape by DataFrame.set_index with DataFrame.stack , explode lists by Series.explode , creare 2 columns DataFrame and last remove duplicates:

df = (df.set_index('AREA')
        .stack()
        .explode()
        .droplevel(1)
        .reset_index(name='total_num')
        .drop_duplicates())
print (df)
      AREA total_num
0    Dhaka         1
1    Dhaka         2
2    Dhaka         3
5    Dhaka         4
6    Dhaka         5
7    Dhaka         6
8   Sylhet        10
9   Sylhet        11
10  Sylhet         7
11  Sylhet         9
14  Sylhet        13