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Pandas 1.x Cookbook

Pandas 1.x Cookbook

By : Matthew Harrison, Theodore Petrou
4.5 (28)
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Pandas 1.x Cookbook

Pandas 1.x Cookbook

4.5 (28)
By: Matthew Harrison, Theodore Petrou

Overview of this book

The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter. This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. Many advanced recipes combine several different features across the pandas library to generate results.
Table of Contents (17 chapters)
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15
Other Books You May Enjoy
16
Index

Introduction

In this chapter, we will dive more into Exploratory Data Analysis (EDA). This is the process of sifting through the data and trying to make sense of the individual columns and the relationships between them.

This activity can be time-consuming, but can also have big payoffs. The better you understand the data, the more you can take advantage of it. If you intend to make machine learning models, having insight into the data can lead to more performant models and understanding why predications are made.

We are going to use a dataset from www.fueleconomy.gov that provides information about makes and models of cars from 1984 through 2018. Using EDA we will explore many of the columns and relationships found in this data.

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