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Python Scikit-learn: Draw a scatterplot, then add a joint density estimate to describe individual distributions on the same plot between Sepal length and Sepal width

Python Machine learning Iris Visualization: Exercise-11 with Solution

Write a Python program to draw a scatterplot, then add a joint density estimate to describe individual distributions on the same plot between Sepal length and Sepal width.

Sample Solution:

Python Code:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
iris = pd.read_csv("iris.csv")
sns.jointplot("SepalLengthCm", "SepalWidthCm", data=iris, color="b").plot_joint(sns.kdeplot, zorder=0, n_levels=6) 
plt.show()

Sample Output:

Python Machine learning Output: Iris Visualization: Exercise-11
 

Python Code Editor:


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Previous: Write a Python program to create a joinplot and add regression and kernel density fits using “reg” to describe individual distributions on the same plot between Sepal length and Sepal width.
Next: Write a Python program to create a joinplot using “kde” to describe individual distributions on the same plot between Sepal length and Sepal width and use ‘+’ sign as marker.

What is the difficulty level of this exercise?



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