sns.histplot : independent percent labels for each category-CodePudding

I have come up with a histogram plot for male and female. I would like the percentage labels of male to add to 100% and also for female.

Below is the code am currently using

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns


data = {
'gender': ['male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female'],
'height': [6, 4, 10, 5, 2, 6, 4, 1, 1, 10, 4, 9, 9, 2, 9, 6, 6, 8, 3, 4, 3, 3, 2, 3, 8, 9, 7, 10, 4, 8, 5, 7, 6, 1, 9, 6, 9, 5, 4, 6, 2, 6, 5, 6, 5, 1, 9, 1, 7, 4]
}

df = pd.DataFrame(data)
df.head(n = 5)


y = sns.histplot(data = df, x = "height", hue ='gender', alpha = 0.5, multiple = "dodge", stat = "percent")
y.bar_label(y.containers[0])
plt.show()

I would appreciate any help. Thanks in advance

CodePudding user response：

Get the height from each container and put it in the list. Then calculate the ratio of the elements to the sum of each list. Specify the list of ratios for each of the bar labels.

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns

data = {
'gender': ['male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'male', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female', 'female'],
'height': [6, 4, 10, 5, 2, 6, 4, 1, 1, 10, 4, 9, 9, 2, 9, 6, 6, 8, 3, 4, 3, 3, 2, 3, 8, 9, 7, 10, 4, 8, 5, 7, 6, 1, 9, 6, 9, 5, 4, 6, 2, 6, 5, 6, 5, 1, 9, 1, 7, 4]
}

df = pd.DataFrame(data)
df.head(n = 5)

y = sns.histplot(data=df, x="height", hue='gender', alpha=0.5, multiple="dodge", stat="percent")

female = []
male = []
for f,m in zip(y.containers[0], y.containers[1]):
    female.append(f.get_height())
    male.append(m.get_height())

print(female)
print(male)

female_per = ['{:.2f}%'.format(x/sum(female)*100) for x in female]
male_per = ['{:.2f}%'.format(x/sum(male)*100) for x in male]
print(female_per)
print(male_per)

y.bar_label(y.containers[0], labels=female_per)
y.bar_label(y.containers[1], labels=male_per)

# y.bar_label(y.containers[0])
# y.bar_label(y.containers[1])

plt.show()

Percentage: