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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

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 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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