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Exploratory Data Analysis with Python Cookbook

You're reading from   Exploratory Data Analysis with Python Cookbook Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781803231105
Length 382 pages
Edition 1st Edition
Languages
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Author (1):
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Ayodele Oluleye Ayodele Oluleye
Author Profile Icon Ayodele Oluleye
Ayodele Oluleye
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Table of Contents (13) Chapters Close

Preface 1. Chapter 1: Generating Summary Statistics 2. Chapter 2: Preparing Data for EDA FREE CHAPTER 3. Chapter 3: Visualizing Data in Python 4. Chapter 4: Performing Univariate Analysis in Python 5. Chapter 5: Performing Bivariate Analysis in Python 6. Chapter 6: Performing Multivariate Analysis in Python 7. Chapter 7: Analyzing Time Series Data in Python 8. Chapter 8: Analysing Text Data in Python 9. Chapter 9: Dealing with Outliers and Missing Values 10. Chapter 10: Performing Automated Exploratory Data Analysis in Python 11. Index 12. Other Books You May Enjoy

Generating box plots for two variables

A boxplot can be used for univariate analysis and bivariate analysis. When analyzing two variables, a boxplot is useful for analyzing numerical-categorical variables. Just like in univariate analysis, the boxplot also gives us a sense of the underlying distribution of a continuous variable through five key metrics. However, in bivariate analysis, the distribution of the continuous variable is displayed across each category of the categorical variable of interest. The five key metrics include the minimum, first quartile, median, third quartile, and maximum. These metrics give insights into the spread of our dataset and possible outliers. The boxplot is explained in more detail in Chapter 4, Performing Univariate Analysis in Python.

In this recipe, we will explore how to create boxplots in seaborn. The boxplot method in seaborn can be used for this.

Getting ready

We will continue working with the Palmer Archipelago (Antarctica) penguin...

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