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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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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

Line chart

Do you remember what a continuous variable is and what a discrete variable is? If not, have a quick look at Chapter 1, Exploratory Data Analysis Fundamentals. Back to the main topic, a line chart is used to illustrate the relationship between two or more continuous variables.

We are going to use the matplotlib library and the stock price data to plot time series lines. First of all, let's understand the dataset. We have created a function using the faker Python library to generate the dataset. It is the simplest possible dataset you can imagine, with just two columns. The first column is Date and the second column is Price, indicating the stock price on that date.

Let's generate the dataset by calling the helper method. In addition to this, we have saved the CSV file. You can optionally load the CSV file using the pandas (read_csv) library and proceed with...

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