import pandas as pd
raw_data = {'regiment': ['Nighthawks', 'Nighthawks', 'Nighthawks', 'Nighthawks', 'Dragoons', 'Dragoons', 'Dragoons', 'Dragoons', 'Scouts', 'Scouts', 'Scouts', 'Scouts'],
'company': ['1st', '1st', '2nd', '2nd', '1st', '1st', '2nd', '2nd','1st', '1st', '2nd', '2nd'],
'name': ['Miller', 'Jacobson', 'Ali', 'Milner', 'Cooze', 'Jacon', 'Ryaner', 'Sone', 'Sloan', 'Piger', 'Riani', 'Ali'],
'preTestScore': [4, 24, 31, 2, 3, 4, 24, 31, 2, 3, 2, 3],
'postTestScore': [25, 94, 57, 62, 70, 25, 94, 57, 62, 70, 62, 70]}
df = pd.DataFrame(raw_data, columns = ['regiment', 'company', 'name', 'preTestScore', 'postTestScore'])
df
regiment | company | name | preTestScore | postTestScore | |
---|---|---|---|---|---|
0 | Nighthawks | 1st | Miller | 4 | 25 |
1 | Nighthawks | 1st | Jacobson | 24 | 94 |
2 | Nighthawks | 2nd | Ali | 31 | 57 |
3 | Nighthawks | 2nd | Milner | 2 | 62 |
4 | Dragoons | 1st | Cooze | 3 | 70 |
5 | Dragoons | 1st | Jacon | 4 | 25 |
6 | Dragoons | 2nd | Ryaner | 24 | 94 |
7 | Dragoons | 2nd | Sone | 31 | 57 |
8 | Scouts | 1st | Sloan | 2 | 62 |
9 | Scouts | 1st | Piger | 3 | 70 |
10 | Scouts | 2nd | Riani | 2 | 62 |
11 | Scouts | 2nd | Ali | 3 | 70 |
12 rows × 5 columns
df.pivot_table(rows=['regiment','company'])
postTestScore | preTestScore | ||
---|---|---|---|
regiment | company | ||
Dragoons | 1st | 47.5 | 3.5 |
2nd | 75.5 | 27.5 | |
Nighthawks | 1st | 59.5 | 14.0 |
2nd | 59.5 | 16.5 | |
Scouts | 1st | 66.0 | 2.5 |
2nd | 66.0 | 2.5 |
6 rows × 2 columns
df.pivot_table(rows=['regiment','company'], aggfunc='count')
company | name | postTestScore | preTestScore | regiment | ||
---|---|---|---|---|---|---|
regiment | company | |||||
Dragoons | 1st | 2 | 2 | 2 | 2 | 2 |
2nd | 2 | 2 | 2 | 2 | 2 | |
Nighthawks | 1st | 2 | 2 | 2 | 2 | 2 |
2nd | 2 | 2 | 2 | 2 | 2 | |
Scouts | 1st | 2 | 2 | 2 | 2 | 2 |
2nd | 2 | 2 | 2 | 2 | 2 |
6 rows × 5 columns