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Pandas 1.x Cookbook

You're reading from Pandas 1.x Cookbook Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python

Product type Paperback

Published in Feb 2020

Publisher Packt

ISBN-13 9781839213106

Length 626 pages

Edition 2nd Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Authors (2):

Theodore Petrou

Matthew Harrison

View More author details

Table of Contents (17) Chapters

Preface

1. Pandas Foundations

2. Essential DataFrame Operations FREE CHAPTER

3. Creating and Persisting DataFrames

4. Beginning Data Analysis

5. Exploratory Data Analysis

6. Selecting Subsets of Data

7. Filtering Rows

8. Index Alignment

9. Grouping for Aggregation, Filtration, and Transformation

10. Restructuring Data into a Tidy Form

11. Combining Pandas Objects

12. Time Series Analysis

13. Visualization with Matplotlib, Pandas, and Seaborn

14. Debugging and Testing Pandas

15. Other Books You May Enjoy

16. Index

Introduction

The goal of this chapter is to introduce a foundation of pandas by thoroughly inspecting the Series and DataFrame data structures. It is important for pandas users to know the difference between a Series and a DataFrame.

The pandas library is useful for dealing with structured data. What is structured data? Data that is stored in tables, such as CSV files, Excel spreadsheets, or database tables, is all structured. Unstructured data consists of free form text, images, sound, or video. If you find yourself dealing with structured data, pandas will be of great utility to you.

In this chapter, you will learn how to select a single column of data from a DataFrame (a two-dimensional dataset), which is returned as a Series (a one-dimensional dataset). Working with this one-dimensional object makes it easy to show how different methods and operators work. Many Series methods return another Series as output. This leads to the possibility of calling further methods in succession...

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Authors (2)

Matthew Harrison

Matthew Harrison

Matt Harrison has been using Python since 2000. He runs MetaSnake, which provides corporate training for Python and Data Science. He is the author of Machine Learning Pocket Reference, the bestselling Illustrated Guide to Python 3, and Learning the Pandas Library, among other books

See other products by Matthew Harrison

Theodore Petrou

Theodore Petrou

Theodore Petrou is the founder of Dunder Data, a training company dedicated to helping teach the Python data science ecosystem effectively to individuals and corporations. Read his tutorials and attempt his data science challenges at the Dunder Data website.

See other products by Theodore Petrou

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