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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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Toc

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

Fancy indexing


Fancy indexing is indexing that does not involve integers or slices, which is conventional indexing. In this tutorial, we will practice fancy indexing to set the diagonal values of the Lena photo to 0. This will draw black lines along the diagonals, crossing through them.

The following is the code for this example:

import scipy.misc 
import matplotlib.pyplot as plt 
 
face = scipy.misc.face() 
xmax = face.shape[0] 
ymax = face.shape[1] 
face=face[:min(xmax,ymax),:min(xmax,ymax)] 
xmax = face.shape[0] 
ymax = face.shape[1] 
face[range(xmax), range(ymax)] = 0 
face[range(xmax-1,-1,-1), range(ymax)] = 0 
plt.imshow(face) 
plt.show() 

The following is a brief explanation of the preceding code:

  1. Set the values of the first diagonal to 0.

    To set the diagonal values to 0, we need to specify two different ranges for the x and y values (coordinates in a Cartesian coordinate system):

            face[range(xmax), range(ymax)] =...
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