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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

Scatter plot

Scatter plots are also called scatter graphs, scatter charts, scattergrams, and scatter diagrams. They use a Cartesian coordinates system to display values of typically two variables for a set of data.

When should we use a scatter plot? Scatter plots can be constructed in the following two situations:

  • When one continuous variable is dependent on another variable, which is under the control of the observer
  • When both continuous variables are independent

There are two important concepts—independent variable and dependent variable. In statistical modeling or mathematical modeling, the values of dependent variables rely on the values of independent variables. The dependent variable is the outcome variable being studied. The independent variables are also referred to as regressors. The takeaway message here is that scatter plots are used when we need to show the...

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