Pandas: How do I create a new index based on a groupby?

Question

Is it possible to transform Table 1 to table 2, where a new multi-index table is created so that a specific 'class_section' grouping has its own index order? Is using group by required? or is there another way I can do this by split.apply.combine technique?

Thanks in advance.

Table 1

	name	movie_watch_count	class_section
0	Morris	2	2
1	Gertie	3	1
2	Kristal	3	1
3	Roslyn	4	2
4	Tari	7	2
5	Dewayne	1	1
6	Edward	6	2
7	Frank	0	2

Table 2

	global_index	group_index	name	movie_watch_count	class_section
0	1	0	Gertie	3	1
1	2	1	Kristal	3	1
2	5	2	Dewayne	1	1
3	0	0	Morris	2	2
4	3	1	Roslyn	4	2
5	4	2	Tari	7	2
6	6	3	Edward	6	2
7	7	4	Frank	0	2

Answer 1

For an independent indexing inside each group we can use groupby(...).cumcount():

from io import StringIO
import pandas as pd

data = '''  name    movie_watch_count   class_section
0   Morris  2   2
1   Gertie  3   1
2   Kristal     3   1
3   Roslyn  4   2
4   Tari    7   2
5   Dewayne     1   1
6   Edward  6   2
7   Frank   0   2'''

df = pd.read_csv(StringIO(data), sep=' \t', engine='python')
df['group_index'] = df.groupby('class_section').cumcount()