Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Python Data Analysis, Second Edition

You're reading from   Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

Arrow left icon
Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Arrow right icon
View More author details
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)] =...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime