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Python Data Analysis

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

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Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
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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 (17) Chapters Close

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

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 (have a look at slicing1d.py in this book's code bundle):

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

We can choose elements from indexes the 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
Published in: Oct 2014
Publisher:
ISBN-13: 9781783553358
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