Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Python Data Analysis

You're reading from   Python Data Analysis Learn how to apply powerful data analysis techniques with popular open source Python modules

Arrow left icon
Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Arrow right icon
View More author details
Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. Statistics and Linear Algebra 4. pandas Primer 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources
Index

Chapter 4. pandas Primer

pandas is named after panel data (an econometric term) and Python data analysis, and is a popular open source Python project. This chapter is a tutorial on basic pandas functionalities, where we will learn about pandas data structures and operations.

Note

The official pandas documentation insists on naming the project pandas in all lowercase letters. The other convention they insist on is this import statement: import pandas as pd. We will try to follow these conventions as much as possible.

In this chapter, we will install and explore pandas. Then, we will acquaint ourselves with the two central pandas data structures: DataFrame and Series. After this, you will learn how to perform SQL-like operations on the data contained in these data structures. pandas has statistical utilities including time-series routines, some of which will be demonstrated. The topics we will pursue are as follows:

  • Installing and exploring pandas
  • DataFrame and Series data structures...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime