Q:

analysing pandas groupby output

I have the following csv file 
Hour, L,  Dr, Tag, Code,   Vge
 0,   L5, XI, PS,  4R,     15
 5,   L5, XI, PS,  4R,     12
 2,   L0, St, v2T, 4R,     11
 8,   L2, TI, sst, 4R,     8
 12,  L5, XI, PS,  4R,     18

I am using the following python code.The idea is to wrap my head around pandas groupby concept.
# !/usr/bin/env python3.4
# -*- coding: utf-8 -*-

import pandas as pd
import pprint

df = pd.read_csv('in.csv')
gb = df.groupby('Hour')
pprint.pprint(list(gb))

This is the output that I get.
 [(0,
      Hour      L    Dr  Tag  Code   Vge
0      0        L5   XI   PS    4R   15),
 (2,
     Hour       L    Dr   Tag  Code     Vge
2     2         L0   St   v2T    4R     11),
 (5,
     Hour       L    Dr  Tag  Code      Vge
1     5         L5   XI   PS    4R      12),
 (8,
     Hour       L    Dr   Tag  Code      Vge
3     8         L2   TI   sst    4R      8),
 (12,
     Hour       L    Dr   Tag  Code     Vge
4    12         L5   XI   PS    4R      18)]

The groupby seems to have inserted 0,1,2,3,4. It would be great if someone can explain what is happening in the data structure.

A:

The 0,1,2,3,4 is the Pandas dataframe internal index

