Dividing multiindex columns by sum to create percentages

Question

I have a dataframe that is created from a pivot table, and looks similar to this:

import pandas as pd
d = {('company1', 'False Negative'): {'April- 2012': 112.0, 'April- 2013': 370.0, 'April- 2014': 499.0, 'August- 2012': 431.0, 'August- 2013': 496.0, 'August- 2014': 221.0},
('company1', 'False Positive'): {'April- 2012': 0.0, 'April- 2013': 544.0, 'April- 2014': 50.0, 'August- 2012': 0.0, 'August- 2013': 0.0, 'August- 2014': 426.0},
('company1', 'True Positive'): {'April- 2012': 0.0, 'April- 2013': 140.0, 'April- 2014': 24.0, 'August- 2012': 0.0, 'August- 2013': 0.0,'August- 2014': 77.0},
('company2', 'False Negative'): {'April- 2012': 112.0, 'April- 2013': 370.0, 'April- 2014': 499.0, 'August- 2012': 431.0, 'August- 2013': 496.0, 'August- 2014': 221.0},
('company2', 'False Positive'): {'April- 2012': 0.0, 'April- 2013': 544.0, 'April- 2014': 50.0, 'August- 2012': 0.0, 'August- 2013': 0.0, 'August- 2014': 426.0},
('company2', 'True Positive'): {'April- 2012': 0.0, 'April- 2013': 140.0, 'April- 2014': 24.0, 'August- 2012': 0.0, 'August- 2013': 0.0,'August- 2014': 77.0},}

df = pd.DataFrame(d)

                company1    company2
                FN  FP  TP  FN  FP  TP
April- 2012     112 0   0   112 0   0
April- 2013     370 544 140 370 544 140
April- 2014     499 50  24  499 50  24
August- 2012    431 0   0   431 0   0
August- 2013    496 0   0   496 0   0
August- 2014    221 426 77  221 426 77

I'm looking to iterative over the upper level of the multiindex column to divide each company by it's sum to create a percentage:

                company1     company2
                FN  FP  TP   FN    FP   TP
April- 2012     1   0   0    1   0  0
April- 2013     .35 .51 .13  .35   .51  .13
April- 2014     .87 .09 .03  .87   .09  .03
etc.

I don't know the company names beforehand. This is a variation of a question asked yesterday: Summing multiple columns with multiindex columns

Answer 1

You can divide by the sum using the div method (with that you can specify the level to match):

df.div(df.sum(axis=1, level=0), level=0)