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Hands-On Exploratory Data Analysis with Python

You're reading from   Hands-On Exploratory Data Analysis with Python Perform EDA techniques to understand, summarize, and investigate your data

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789537253
Length 352 pages
Edition 1st Edition
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Authors (2):
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Suresh Kumar Mukhiya Suresh Kumar Mukhiya
Author Profile Icon Suresh Kumar Mukhiya
Suresh Kumar Mukhiya
Usman Ahmed Usman Ahmed
Author Profile Icon Usman Ahmed
Usman Ahmed
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: The Fundamentals of EDA
2. Exploratory Data Analysis Fundamentals FREE CHAPTER 3. Visual Aids for EDA 4. EDA with Personal Email 5. Data Transformation 6. Section 2: Descriptive Statistics
7. Descriptive Statistics 8. Grouping Datasets 9. Correlation 10. Time Series Analysis 11. Section 3: Model Development and Evaluation
12. Hypothesis Testing and Regression 13. Model Development and Evaluation 14. EDA on Wine Quality Data Analysis 15. Other Books You May Enjoy Appendix

Data analysis

This is the most important part of EDA. This is the part where we gain insights from the data that we have.

Let's answer the following questions one by one:

  1. How many emails did I send during a given timeframe?
  2. At what times of the day do I send and receive emails with Gmail?
  3. What is the average number of emails per day?
  4. What is the average number of emails per hour?
  5. Whom do I communicate with most frequently?
  6. What are the most active emailing days?
  7. What am I mostly emailing about?

In the following sections, we will answer the preceding questions.

Number of emails

The answer to the first question, "How many emails did I send during a given timeframe?", can be answered as shown here:

print(dfs...
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