How to add percentages on top of bars in seaborn

Question

Given the following count plot how do I place percentages on top of the bars?

import seaborn as sns sns.set(style="darkgrid") titanic = sns.load_dataset("titanic") ax = sns.countplot(x="class", hue="who", data=titanic) 

For example for "First" I want total First men/total First, total First women/total First, and total First children/total First on top of their respective bars.

Answer 1

The seaborn.catplot organizing function returns a FacetGrid, which gives you access to the fig, the ax, and its patches. If you add the labels when nothing else has been plotted you know which bar-patches came from which variables. From @LordZsolt's answer I picked up the order argument to catplot: I like making that explicit because now we aren't relying on the barplot function using the order we think of as default.

import seaborn as sns from itertools import product  titanic = sns.load_dataset("titanic")  class_order = ['First','Second','Third']  hue_order = ['child', 'man', 'woman'] bar_order = product(class_order, hue_order)  catp = sns.catplot(data=titanic, kind='count',                     x='class', hue='who',                    order = class_order,                     hue_order = hue_order )  # As long as we haven't plotted anything else into this axis, # we know the rectangles in it are our barplot bars # and we know the order, so we can match up graphic and calculations:  spots = zip(catp.ax.patches, bar_order) for spot in spots:     class_total = len(titanic[titanic['class']==spot[1][0]])     class_who_total = len(titanic[(titanic['class']==spot[1][0]) &          (titanic['who']==spot[1][1])])     height = spot[0].get_height()      catp.ax.text(spot[0].get_x(), height+3, '{:1.2f}'.format(class_who_total/class_total))      #checking the patch order, not for final:     #catp.ax.text(spot[0].get_x(), -3, spot[1][0][0]+spot[1][1][0]) 

produces

An alternate approach is to do the sub-summing explicitly, e.g. with the excellent pandas, and plot with matplotlib, and also do the styling yourself. (Though you can get quite a lot of styling from sns context even when using matplotlib plotting functions. Try it out -- )

Answer 2

with_hue function will plot percentages on the bar graphs if you have the 'hue' parameter in your plots. It takes the actual graph, feature, Number_of_categories in feature, and hue_categories(number of categories in hue feature) as a parameter.

without_hue function will plot percentages on the bar graphs if you have a normal plot. It takes the actual graph and feature as a parameter.

def with_hue(ax, feature, Number_of_categories, hue_categories):     a = [p.get_height() for p in ax.patches]     patch = [p for p in ax.patches]     for i in range(Number_of_categories):         total = feature.value_counts().values[i]         for j in range(hue_categories):             percentage = '{:.1f}%'.format(100 * a[(j*Number_of_categories + i)]/total)             x = patch[(j*Number_of_categories + i)].get_x() + patch[(j*Number_of_categories + i)].get_width() / 2 - 0.15             y = patch[(j*Number_of_categories + i)].get_y() + patch[(j*Number_of_categories + i)].get_height()              ax.annotate(percentage, (x, y), size = 12)  def without_hue(ax, feature):     total = len(feature)     for p in ax.patches:         percentage = '{:.1f}%'.format(100 * p.get_height()/total)         x = p.get_x() + p.get_width() / 2 - 0.05         y = p.get_y() + p.get_height()         ax.annotate(percentage, (x, y), size = 12)