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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

Performing Univariate Analysis in Python

When performing univariate analysis, we are usually interested in analyzing one or more variables in our dataset individually. Some insights we can glean during univariate analysis include the median, mode, maximum, range, and outliers. Univariate analysis can be performed on both categorical and numerical variables. Several chart options can be explored for both types of variables. These chart options can help us understand the underlying distribution of our data and identify any hidden patterns within the dataset. It is important to understand when to use each chart as this will ensure the accuracy of our analysis and the insights we derive from it.

In this chapter, we will cover the following:

  • Performing univariate analysis using a histogram
  • Performing univariate analysis using a boxplot
  • Performing univariate analysis using a violin plot
  • Performing univariate analysis using a summary table
  • Performing univariate...
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