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

Issue

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?

Solution

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)

Answered By - fanfabbb