Seaborn Distribution/Histogram Plot – Tutorial and Examples
Introduction
Seaborn is one of the most widely used data visualization libraries in Python, as an extension to Matplotlib. It offers a simple, intuitive, yet highly customizable API for data visualization.
In this tutorial, we’ll take a look at how to plot a histogram plot in Seaborn. We’ll cover how to plot a histogram with Seaborn, how to change Histogram bin sizes, as well as plot Kernel Density Estimation plots on top of Histograms and show distribution data instead of count data.
Import Data
We’ll be using the Netflix Shows dataset and visualizing the distributions from there.
Let’s import Pandas and load in the dataset:
import pandas as pd
df = pd.read_csv('netflix_titles.csv')
How to Plot a Histogram with Seaborn?
Well, Seaborn doesn’t have a regular histplot() function anymore. Specifically, Seaborn has different types of distribution plots that you might want