I would like to add percent values - in addition to counts - to my pandas barplot. However, I am not able to do so. My code is shown below and thus far I can get count values to display. Can somebody please help me add relative % values next to/below the count values displayed for each bar?
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('ggplot')
import seaborn as sns
sns.set_style("white")
fig = plt.figure()
fig.set_figheight(5)
fig.set_figwidth(10)
ax = fig.add_subplot(111)
counts = [29227, 102492, 53269, 504028, 802994]
y_ax = ('A','B','C','D','E')
y_tick = np.arange(len(y_ax))
ax.barh(range(len(counts)), counts, align = "center", color = "tab:blue")
ax.set_yticks(y_tick)
ax.set_yticklabels(y_ax, size = 8)
#annotate bar plot with values
for i in ax.patches:
ax.text(i.get_width()+.09, i.get_y()+.3, str(round((i.get_width()), 1)), fontsize=8)
sns.despine()
plt.show();
The output of my code is shown below. How can one add % values next to each count value displayed?
Our steps will be: Iterate over the bars. Get the x-axis position(x) and the width(w) of the bar this will help us to get the x coordinate of the text i.e. get_x()+get_width()/2. The y-coordinate(y) of the text can be found using the height of the bar i.e. get_height()
To annotate bars in barplot made with Seaborn, we will use Matplotlib's annotate function. Matplotlib's annotate() function is pretty versatile and we can customize various aspects of annotation in a plot.
To add annotation, we first need to make grouped barplot before and then use Matplotlib's annotate function to add text for bars in grouped barplot. The “patches” attribute in Seaborn/Matplotlib object gives us access to each bar in barplot.
With Pandas plot() , labelling of the axis is achieved using the Matplotlib syntax on the “plt” object imported from pyplot. The key functions needed are: “xlabel” to add an x-axis label. “ylabel” to add a y-axis label.
pandas
pandas v1.2.4
import pandas as pd
import matplotlib.pyplot as plt
# create the dataframe from values in the OP
counts = [29227, 102492, 53269, 504028, 802994]
df = pd.DataFrame(data=counts, columns=['counts'], index=['A','B','C','D','E'])
# add a percent column
df['%'] = df.counts.div(df.counts.sum()).mul(100).round(2)
# display(df)
counts %
A 29227 1.96
B 102492 6.87
C 53269 3.57
D 504028 33.78
E 802994 53.82
matplotlib
from version 3.4.2matplotlib.pyplot.bar_label
.bar_label
.pandas v1.2.4
, which is using matplotlib
as the plot engine.fmt
parameter, but more sophisticated formatting should be done with the labels
parameter.ax = df.plot(kind='barh', y='counts', figsize=(10, 5), legend=False, width=.75,
title='This is the plot generated by all code examples in this answer')
# customize the label to include the percent
labels = [f' {v.get_width()}\n {df.iloc[i, 1]}%' for i, v in enumerate(ax.containers[0])]
# set the bar label
ax.bar_label(ax.containers[0], labels=labels, label_type='edge', size=13)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
plt.show()
matplotlib
before version 3.4.2# plot the dataframe
ax = df.plot(kind='barh', y='counts', figsize=(10, 5), legend=False, width=.75)
for i, y in enumerate(ax.patches):
# get the percent label
label_per = df.iloc[i, 1]
# add the value label
ax.text(y.get_width()+.09, y.get_y()+.3, str(round((y.get_width()), 1)), fontsize=10)
# add the percent label here
ax.text(y.get_width()+.09, y.get_y()+.1, str(f'{round((label_per), 2)}%'), fontsize=10)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
plt.show()
pandas
matplotlib v3.3.4
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(10, 5))
counts = [29227, 102492, 53269, 504028, 802994]
# calculate percents
percents = [100*x/sum(counts) for x in counts]
y_ax = ('A','B','C','D','E')
y_tick = np.arange(len(y_ax))
ax.barh(range(len(counts)), counts, align = "center", color = "tab:blue")
ax.set_yticks(y_tick)
ax.set_yticklabels(y_ax, size = 8)
#annotate bar plot with values
for i, y in enumerate(ax.patches):
label_per = percents[i]
ax.text(y.get_width()+.09, y.get_y()+.3, str(round((y.get_width()), 1)), fontsize=10)
# add the percent label here
# ax.text(y.get_width()+.09, y.get_y()+.3, str(round((label_per), 2)), ha='right', va='center', fontsize=10)
ax.text(y.get_width()+.09, y.get_y()+.1, str(f'{round((label_per), 2)}%'), fontsize=10)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
plt.show()
\n
in between to get a "natural" line spacing:str(f'{round((y.get_width()), 1)}\n{round((label_per), 2)}%')
ax.text(..., va='center')
to vertically center and be able to use a slightly larger font.ax.set_xlim(0, max(counts) * 1.18)
to get a bit more space for the text.str(f' {round((label_per), 2)}%')
, note the space before {
.y.get_width()+.09
is extremely close to y.get_width()
when these values are in the tens of thousands.If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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