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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
Languages
Tools
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Authors (2):
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 Kumar Mukhiya Kumar Mukhiya
Author Profile Icon Kumar Mukhiya
Kumar Mukhiya
 Ahmed Ahmed
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Ahmed
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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

Getting started with EDA

As mentioned earlier, we are going to use Python as the main tool for data analysis. Yay! Well, if you ask me why, Python has been consistently ranked among the top 10 programming languages and is widely adopted for data analysis and data mining by data science experts. In this book, we assume you have a working knowledge of Python. If you are not familiar with Python, it's probably too early to get started with data analysis. I assume you are familiar with the following Python tools and packages:

Python programming

Fundamental concepts of variables, string, and data types

Conditionals and functions

Sequences, collections, and iterations

Working with files

Object-oriented programming

NumPy

Create arrays with NumPy, copy arrays, and divide arrays

Perform different operations on NumPy arrays

Understand array selections, advanced indexing...

You have been reading a chapter from
Hands-On Exploratory Data Analysis with Python
Published in: Mar 2020
Publisher: Packt
ISBN-13: 9781789537253
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