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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

Pivot tables and cross-tabulations

Pandas offers several options for grouping and summarizing data. We've already discussed groupby, aggregation, and transformation, but there are other options available, such as pivot_table and crosstab. First, let's understand pivot tables.

Pivot tables

The pandas.pivot_table() function creates a spreadsheet-style pivot table as a dataframe. The levels in the pivot table will be stored in MultiIndex objects (hierarchical indexes) on the index and columns of the resulting dataframe.

The simplest pivot tables must have a dataframe and an index/list of the index. Let's take a look at how to do this:

  1. Let's make a pivot table of a new dataframe that consists of the body-style...
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