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Python Data Analysis, Second Edition

You're reading from Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

Product type Paperback

Published in Mar 2017

Publisher Packt

ISBN-13 9781787127487

Length 330 pages

Edition 2nd Edition

Languages

Python

Tools

Scikit-learn

Concepts

Data Analysis

Author (1):

Ivan Idris

View More author details

Table of Contents (16) Chapters

Preface

1. Getting Started with Python Libraries

2. NumPy Arrays FREE CHAPTER

3. The Pandas Primer

4. Statistics and Linear Algebra

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

Chapter 3. The Pandas Primer

The Pandas is named after panel data (an econometric term) and Python data analysis, and is a popular open source Python library. We shall learn about basic Pandas functionalities, data structures, and operations in this chapter.

The official Pandas documentation insists on naming the project pandas in all lowercase letters. The other convention the Pandas project insists on is the import pandas as pd import statement.

We will follow these conventions in this text.

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 that, 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 look at are as follows:

Installing and exploring Pandas
The Panda DataFrames
The Panda Series
Querying data in Pandas...

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Authors (1)

Idris

Idris

Ivan Idris has an MSc in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a Java developer, data warehouse developer, and QA analyst. His main professional interests are business intelligence, big data, and cloud computing. Ivan Idris enjoys writing clean, testable code and interesting technical articles. Ivan Idris is the author of NumPy 1.5. Beginner's Guide and NumPy Cookbook by Packt Publishing.

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