Pandas percentage of total with groupby

Question

This is obviously simple, but as a numpy newbe I\'m getting stuck.

I have a CSV file that contains 3 columns, the State, the Office ID, and the Sales for that office

Answer 1

You can sum the whole DataFrame and divide by the state total:

# Copying setup from Paul H answer
import numpy as np
import pandas as pd
np.random.seed(0)
df = pd.DataFrame({'state': ['CA', 'WA', 'CO', 'AZ'] * 3,
               'office_id': list(range(1, 7)) * 2,
               'sales': [np.random.randint(100000, 999999) for _ in range(12)]})
# Add a column with the sales divided by state total sales.
df['sales_ratio'] = (df / df.groupby(['state']).transform(sum))['sales']

df

Returns

    office_id   sales state  sales_ratio
0           1  405711    CA     0.193319
1           2  535829    WA     0.347072
2           3  217952    CO     0.198743
3           4  252315    AZ     0.192500
4           5  982371    CA     0.468094
5           6  459783    WA     0.297815
6           1  404137    CO     0.368519
7           2  222579    AZ     0.169814
8           3  710581    CA     0.338587
9           4  548242    WA     0.355113
10          5  474564    CO     0.432739
11          6  835831    AZ     0.637686

But note that this only works because all columns other than state are numeric, enabling summation of the entire DataFrame. For example, if office_id is character instead, you get an error:

df.office_id = df.office_id.astype(str)
df['sales_ratio'] = (df / df.groupby(['state']).transform(sum))['sales']

TypeError: unsupported operand type(s) for /: 'str' and 'str'