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

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)

I think I would probably do this in one go (without importing division):

1. * df.sex.value_counts() / len(df.sex)

or perhaps, remembering you want a percentage:

100. * df.sex.value_counts() / len(df.sex)

Much of a muchness really, your way looks fine too.

If you want to merge counts with percentage, can use:

c = df.sex.value_counts(dropna=False)
p = df.sex.value_counts(dropna=False, normalize=True)
pd.concat([c,p], axis=1, keys=['counts', '%'])