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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

Implementing Automated EDA using custom functions

Sometimes, when performing Automated EDA, we may require more flexibility around the visual options and analysis techniques. In such cases, custom functions may be preferable to the libraries discussed in the preceding recipes since they may be limited in providing such flexibility. We can write custom functions using the preferred visual options and analysis techniques and save them as a Python module. The module ensures our code is reusable, which means we can easily perform EDA automatically without having to write several lines of code. This gives us significant flexibility, especially because the module can be constantly improved based on preferences. Most of the heavy lifting happens only when we are initially writing the custom functions. Once they have been saved into a module, they become reusable, and we only need to call the functions in single lines of code.

We will explore how to write custom functions to perform Automated...

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