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Contour Plot using Seaborn in Python


In this tutorial, we will learn about what is contour plot and how to install Seaborn Library. We will also learn about different methods to plot contour plots.

What is a contour plot?

It is one of the data visualization techniques that is used to represent three-dimensional data in a two-dimensional plane. It can be visualized using matplotlib as well as the seaborn library in Python. We will see different methods to visualize contour plots using Seaborn.

Installing Seaborn Library

pip install seaborn

This will install the latest version of the Seaborn library in your system.

Different methods to create contour plots

1) Using a joint plot

It is used to visualize the joint distribution of given two variables. We can plot it using the following code

Importing required libraries

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

In the above code seaborn library that we are importing, we use it to visualize joint plots. Numpy to perform operations on numeric data. Matplotlib to customize the graph.

Creating random values for our variables

np.random.seed(42)  
x1 = np.random.randn(1000)
y1 = np.random.randn(1000)

In the above we are setting the seed as 42 to ensure each time we run the code, we will get the same sequence of random numbers. Then usinsg np.random.randn function we are generating a random sequence of numbers. Here we are generating just random data. You can use your data in Excel or CSV file using a pandas data frame.

Plotting joint plot

g = sns.jointplot(x=x1, y=y1,kind="kde",)
plt.show()

In the above code, we are providing parameters x and y  with variables x1 and y1 respectively. We are setting kind=’kde’ means kernel density estimation distribution of variables x and y. We are not using the z variable here as it will automatically be created by this KDE function.

Output

Contour Plot using Seaborn in PythonContour Plot using Seaborn in Python

2) Using kdeplot

It directly uses the kernel density estimation(KDE) function for the joint distribution of x and y. KDE is used when the distribution function of a variable is not known.

We can plot contour using the following code

sns.kdeplot(x=x1,y=y1)
plt.show()

Output

contour plot in seaborn Using kdeplotcontour plot in seaborn Using kdeplot

As in the previous code, we are providing values to the x and y parameters.



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