# Import modules
import pandas as pd
# Example dataframe
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 |
# Create a grouping object. In other words, create an object that
# represents that particular grouping. In this case we group
# pre-test scores by the regiment.
regiment_preScore = df['preTestScore'].groupby(df['regiment'])
# Display the mean value of the each regiment's pre-test score
regiment_preScore.mean()
regiment Dragoons 15.50 Nighthawks 15.25 Scouts 2.50 dtype: float64