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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 2. NumPy Arrays

Now that we have worked on a real example utilizing the foundational data analysis libraries from SciPy stack, it's time to learn about NumPy arrays. This chapter acquaints you with the fundamentals of NumPy arrays. At the end of this chapter, you will have a basic understanding of NumPy arrays and related functions.

The topics we will address in this chapter are as follows:

  • The NumPy array object
  • Creating a multidimensional array
  • Selecting NumPy array elements
  • NumPy numerical types
  • One-dimensional slicing and indexing
  • Manipulating array shapes
  • Creating array views and copies
  • Fancy indexing
  • Indexing with a list of locations
  • Indexing NumPy arrays with Booleans
  • Broadcasting NumPy arrays

You may want to open the ch-02.ipynb file in Jupyter Notebook to follow along the examples in this chapter or type them in a new notebook of your own.

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