如何组合两个直方图python

Question

male[['Gender','Age']].plot(kind='hist', x='Gender', y='Age', bins=50)
female[['Gender','Age']].plot(kind='hist', x='Gender', y='Age', bins=50)

So basically, I used data from a file to create two histograms based on gender and age. From the beginning I separated the data by gender to initially plot. Now i'm having a hard time putting the two histograms together.

Answer 1

As mentioned in the comment, you can use matplotlib to do this task. I haven't figured out how to plot two histogram using Pandas tho (would like to see how people have done that).

import matplotlib.pyplot as plt
import random

# example data
age = [random.randint(20, 40) for _ in range(100)]
sex = [random.choice(['M', 'F']) for _ in range(100)]

# just give a list of age of male/female and corresponding color here
plt.hist([[a for a, s in zip(age, sex) if s=='M'], 
          [a for a, s in zip(age, sex) if s=='F']], 
         color=['b','r'], alpha=0.5, bins=10)
plt.show()

Answer 2

Consider converting the dataframes to a two-column numpy matrix as matplotlib 's hist works with this structure instead of two different length pandas dataframes with non-numeric columns. Pandas' join is used to bind the two columns, MaleAge and FemaleAge .

Here, the Gender indicator is removed and manually labeled according to the column order.

import numpy as np
import pandas as pd
from matplotlib import pyplot as plt

...
# RESET INDEX AND RENAME COLUMN AFTER SUBSETTING
male = df2[df2['Gender'] == "M"].reset_index(drop=True).rename(columns={'Age':'MaleAge'})
female = df2[df2['Gender'] == "F"].reset_index(drop=True).rename(columns={'Age':'FemaleAge'})

# OUTER JOIN TO ACHIEVE SAME LENGTH
gendermat = np.array(male[['MaleAge']].join(female[['FemaleAge']], how='outer'))

plt.hist(gendermat, bins=50, label=['male', 'female'])
plt.legend(loc='upper right')
plt.show()
plt.clf()
plt.close()