Given a pandas Series that represents frequencies of a value, how can I turn those frequencies into percentages?

Question

I was experimenting with the kaggle.com Titanic data set (data on every person on the Titanic) and came up with a gender breakdown like this:

df = pd.DataFrame({'sex': ['male'] * 577 + ['female'] * 314}) gender = df.sex.value_counts() gender  male   577 female 314  

I would like to find out the percentage of each gender on the Titanic.

My approach is slightly less than ideal:

from __future__ import division pcts = gender / gender.sum() pcts  male      0.647587 female    0.352413 

Is there a better (more idiomatic) way?

Answer 1

This function is implemented in pandas, actually even in value_counts(). No need to calculate :)

just type:

df.sex.value_counts(normalize=True) 

which gives exactly the desired output.

Please note that value_counts() excludes NA values, so numbers might not add up to 1. See here: http://pandas-docs.github.io/pandas-docs-travis/generated/pandas.Series.value_counts.html (A column of a DataFrame is a Series)