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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 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

One-dimensional slicing and indexing


Slicing of one-dimensional NumPy arrays works just like the slicing of standard Python lists. Let's define an array containing the numbers 0, 1, 2, and so on up to and including 8. We can select a part of the array from indexes 3 to 7, which extracts the elements of the arrays 3 through 6:

In: a = np.arange(9) 
In: a[3:7] 
Out: array([3, 4, 5, 6]) 

We can choose elements from an index of 0 to 7 with an increment of 2:

In: a[:7:2] 
Out: array([0, 2, 4, 6]) 

Just as in Python, we can use negative indices and reverse the array:

In: a[::-1] 
Out: array([8, 7, 6, 5, 4, 3, 2, 1, 0]) 
You have been reading a chapter from
Python Data Analysis, Second Edition - Second Edition
Published in: Mar 2017
Publisher: Packt
ISBN-13: 9781787127487
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