Seaborn countplot with normalized y axis per group

Question

I was wondering if it is possible to create a Seaborn count plot, but instead of actual counts on the y-axis, show the relative frequency (percentage) within its group (as s

Answer 1

I might be confused. The difference between your output and the output of

occupation_counts = (df.groupby(['income'])['occupation']
                     .value_counts(normalize=True)
                     .rename('percentage')
                     .mul(100)
                     .reset_index()
                     .sort_values('occupation'))
p = sns.barplot(x="occupation", y="percentage", hue="income", data=occupation_counts)
_ = plt.setp(p.get_xticklabels(), rotation=90)  # Rotate labels

is, it seems to me, only the order of the columns.

And you seem to care about that, since you pass sort=False. But then, in your code the order is determined uniquely by chance (and the order in which the dictionary is iterated even changes from run to run with Python 3.5).