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Python Scikit-learn: Create a joinplot to describe individual distributions on the same plot between Sepal length and Sepal width

Python Machine learning Iris Visualization: Exercise-8 with Solution

Write a Python program to create a joinplot to describe individual distributions on the same plot between Sepal length and Sepal width.

Note: The bivariate analogue of a histogram is known as a “hexbin” plot, because it shows the counts of observations that fall within hexagonal bins. This plot works best with relatively large datasets. It’s available through the matplotlib plt.hexbin function and as a style in jointplot(). It looks best with a white background.

Sample Solution:

Python Code:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
iris = pd.read_csv("iris.csv")
fig=sns.jointplot(x='SepalLengthCm', y='SepalWidthCm', kind="hex", color="red", data=iris)
plt.show()

Output:

Python Machine learning Output: Iris Visualization: Exercise-8
 

Python Code Editor:


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