Python Scikit-learn: Create a kde plot of two shaded bivariate densities of Sepal Width and Sepal Length
Python Machine learning Iris Visualization: Exercise-16 with Solution
Write a Python program using seaborne to create a kde (Kernel Density Estimate) plot of two shaded bivariate densities of Sepal Width and Sepal Length.
Sample Solution:
Python Code:
# Import necessary modules
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
iris = pd.read_csv("iris.csv")
#Drop id column
iris = iris.drop('Id',axis=1)
sns.kdeplot(data=sub[['PetalLengthCm','PetalWidthCm']],cmap="plasma", shade=True, shade_lowest=False)
plt.title('Iris-setosa')
plt.xlabel('Petal Length Cm')
plt.ylabel('Petal Width Cm')
plt.show()
Output:
Python Code Editor:
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Next: Write a Python program to find the correlation between variables of iris data. Also create a hitmap using Seaborn to present their relations.What is the difficulty level of this exercise?
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