Berne Berne - 4 months ago 17x
Python Question

Python Pandas - dummy variables when not all categories are present

I have a set of dataframes where one of the columns contains a categorical variable. I'd like to convert it to several dummy variables, in which case I'd normally use


What happens is that
looks at the data available in each dataframe to find out how many categories there are, and thus create the appropriate number of dummy variables. However, in the problem I'm working right now, I actually know in advance what the possible categories are. But when looking at each dataframe individually, not all categories necessarily appear.

My question is: is there a way to pass to
(or an equivalent function) the names of the categories, so that, for the categories that don't appear in a given dataframe, it'd just create a column of 0s?

Something that would make this:

categories = ['a', 'b', 'c']

1 a
2 b
3 a

Become this:

cat_a cat_b cat_c
1 1 0 0
2 0 1 0
3 1 0 0


Using transpose and reindex

import pandas as pd

cats = ['a', 'b', 'c']
df = pd.DataFrame({'cat': ['a', 'b', 'a']})

dummies = pd.get_dummies(df, prefix='', prefix_sep='')
dummies = dummies.T.reindex(cats).T.fillna(0)

print dummies

    a    b    c
0  1.0  0.0  0.0
1  0.0  1.0  0.0
2  1.0  0.0  0.0