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Pandas Cookbook

You're reading from   Pandas Cookbook Practical recipes for scientific computing, time series, and exploratory data analysis using Python

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Product type Paperback
Published in Oct 2024
Publisher Packt
ISBN-13 9781836205876
Length 404 pages
Edition 3rd Edition
Languages
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Authors (2):
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William Ayd William Ayd
Author Profile Icon William Ayd
William Ayd
Matthew Harrison Matthew Harrison
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Matthew Harrison
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Table of Contents (13) Chapters Close

Preface 1. pandas Foundations FREE CHAPTER 2. Selection and Assignment 3. Data Types 4. The pandas I/O System 5. Algorithms and How to Apply Them 6. Visualization 7. Reshaping DataFrames 8. Group By 9. Temporal Data Types and Algorithms 10. General Usage and Performance Tips 11. The pandas Ecosystem 12. Index

Exploratory data analysis

Oftentimes, you will find yourself provided with a dataset that you know very little about. Throughout this book, we’ve shown ways to manually sift through data, but there are also tools out there that can help automate potentially tedious tasks and help you grasp the data in a shorter amount of time.

YData Profiling

YData Profiling bills itself as the “leading package for data profiling, that automates and standardizes the generation of detailed reports, complete with statistics and visualizations.” While we discovered how to manually explore data back in the chapter on visualization, this package can be used as a quick-start to automatically generate many useful reports and features.

To compare this to some of the work we did in those chapters, let’s take another look at the vehicles dataset. For now, we are just going to pick a small subset of columns to keep our YData Profiling minimal; for large datasets, the performance...

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