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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

Selecting NumPy array elements

From time to time, we will wish to select a specific constituent of an array. We will take a look at how to do this, but to kick off, let's make a 2x2 matrix again:

In: a = np.array([[1,2],[3,4]]) 
In: a 
Out: 
array([[1, 2], 
       [3, 4]]) 

The matrix was made this time by giving the array() function a list of lists. We will now choose each item of the matrix one at a time, as shown in the following code snippet. Recall that the index numbers begin from 0:

In: a[0,0] 
Out: 1 
In: a[0,1] 
Out: 2 
In: a[1,0] 
Out: 3 
In: a[1,1] 
Out: 4 

As you can see, choosing elements of an array is fairly simple. For the array a, we just employ the notation a[m,n], where m and n are the indices of the item in the array. Have a look at the following figure for your reference:

Selecting NumPy array elements

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