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Python Scikit-learn: Create a hitmap using Seaborn to present their relations

Python Machine learning Iris Visualization: Exercise-17 with Solution

Write a Python program to find the correlation between variables of iris data. Also create a hitmap using Seaborn to present their relations.

Sample Solution:

Python Code:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
iris = pd.read_csv("iris.csv")
#Drop id column
iris = iris.drop('Id',axis=1)
X = iris.iloc[:, 0:4]
f, ax = plt.subplots(figsize=(10, 8))
corr = X.corr()
print(corr)
sns.heatmap(corr, mask=np.zeros_like(corr, dtype=np.bool), 
          cmap=sns.diverging_palette(220, 10, as_cmap=True),square=True, ax=ax, linewidths=.5)
plt.show() 

Output:

Python Machine learning Output: Iris Visualization: Exercise-17
 

Python Code Editor:


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Previous: 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.

Next: Write a Python program to create a box plot (or box-and-whisker plot) which shows the distribution of quantitative data in a way that facilitates comparisons between variables or across levels of a categorical variable of iris dataset. Use seaborn.

What is the difficulty level of this exercise?