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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

Analysing Text Data in Python

Very often, we will need to perform exploratory data analysis on text data. The amount of digital data created in the world today has increased significantly, and text data forms a substantial proportion of this digital data. Some common examples we see every day include emails, social media posts, and text messages. Text data is classified as unstructured data because it usually doesn’t appear in rows and columns.

In previous chapters, we focused on exploratory data analysis techniques for structured data (i.e., data that appears in rows and columns). However, in the chapter, we will focus on exploratory data analysis techniques for a very common type of unstructured data – text data.

In this chapter, we will discuss common techniques to prepare and analyze text data. The chapter includes the following:

  • Preparing text data
  • Removing stop words
  • Analyzing part of speech (POS)
  • Performing stemming and lemmatization
  • ...
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