You can use the following basic syntax to display percentages on the y-axis of a pandas histogram:

import pandas as pd
import numpy as np
import matplotlib.pyplotas plt
from matplotlib.tickerimport PercentFormatter

#create histogram, using percentages instead of counts
plt.hist(df['my_column'], weights=np.ones(len(df)) / len(df))

#apply percentage format to y-axis
plt.gca().yaxis.set_major_formatter(PercentFormatter(1))
plt.show()

The following example shows how to use this syntax in practice.

Example: Display Percentage on Y-Axis of Pandas Histogram

Suppose we have the following pandas DataFrame that contains information about various basketball players:

import pandas as pd
import numpy as np

#make this example reproducible
np.random.seed(1)

#create DataFrame
df = pd.DataFrame({'points': np.random.normal(loc=20, scale=2, size=300),
                   'assists': np.random.normal(loc=14, scale=3, size=300),
                   'rebounds': np.random.normal(loc=12, scale=1, size=300)})

#view head of DataFrame
print(df.head())

      points    assists   rebounds
0  23.248691  20.197350  10.927036
1  18.776487   9.586529  12.495159
2  18.943656  11.509484  11.047938
3  17.854063  11.358267  11.481854
4  21.730815  13.162707  10.538596

If we create a histogram to visualize the distribution of values in the points column, the y-axis will display counts by default:

import matplotlib.pyplot as plt 

#create histogram for points columb
plt.hist(df['points'], edgecolor='black')

To instead display percentages on the y-axis, we can use the PercentFormatter function:

import numpy as np
import matplotlib.pyplotas plt
from matplotlib.tickerimport PercentFormatter

#create histogram, using percentages instead of counts
plt.hist(df['points'], weights=np.ones(len(df)) / len(df), edgecolor='black')

#apply percentage format to y-axis
plt.gca().yaxis.set_major_formatter(PercentFormatter(1))
plt.show()

Notice that the y-axis now displays percentages.

If you’d like to remove the decimals from the percentages, simply use the argument decimals=0 within the PercentFormatter() function:

import numpy as np
import matplotlib.pyplotas plt
from matplotlib.tickerimport PercentFormatter

#create histogram, using percentages instead of counts
plt.hist(df['points'], weights=np.ones(len(df)) / len(df), edgecolor='black')

#apply percentage format to y-axis
plt.gca().yaxis.set_major_formatter(PercentFormatter(1, decimals=0))
plt.show()

The y-axis now displays percentages without any decimals.

The following tutorials explain how to perform other common tasks in pandas: