Seaborn Histogram

You can easily create and style a histogram in Seaborn with just a few steps. Let’s get started. You will need a few dependencies to ensure that the plot is shown.  The dependencies that you essentially need to load are Matplotlib and Seaborn. However, let’s load the standards such as Pandas and Numpy also in case there is a need to change the data set to use the Seaborn histogram. For this example, I am using the NBA players dataset that you can find on Kaggle.com. I am interested in the height distribution from 1950 to 2018.

 

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

Next, let’s access the Seaborn histograms which is  produced by the attribute distplot

sns.distplot(df['height'])

the default histogram in Seaborn give a nice plot

This is the default histogram plot that has the default bins. You can also customize the number of bins using the bins parameter in your function.

sns.distplot(df['height'], bins=20)

you can alter the number of bins

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