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Python Scikit-learn: Create a box 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

Python Machine learning Iris Visualization: Exercise-18 with Solution

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.

Sample Solution:

Python Code:

import pandas as pd
import seaborn as sns 
iris = pd.read_csv("iris.csv")
#Drop id column
iris = iris.drop('Id',axis=1)
box_data = iris #variable representing the data array
box_target = iris.Species #variable representing the labels array
sns.boxplot(data = box_data,width=0.5,fliersize=5)
sns.set(rc={'figure.figsize':(2,15)})

Output:

Python Machine learning Output: Iris Visualization: Exercise-18
 

Python Code Editor:


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

Next: Write a Python program to create a Principal component analysis (PCA) of iris dataset.

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