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Hands-On Data Science with Anaconda

You're reading from   Hands-On Data Science with Anaconda Utilize the right mix of tools to create high-performance data science applications

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788831192
Length 364 pages
Edition 1st Edition
Languages
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Authors (2):
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James Yan James Yan
Author Profile Icon James Yan
James Yan
Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Table of Contents (15) Chapters Close

Preface 1. Ecosystem of Anaconda 2. Anaconda Installation FREE CHAPTER 3. Data Basics 4. Data Visualization 5. Statistical Modeling in Anaconda 6. Managing Packages 7. Optimization in Anaconda 8. Unsupervised Learning in Anaconda 9. Supervised Learning in Anaconda 10. Predictive Data Analytics – Modeling and Validation 11. Anaconda Cloud 12. Distributed Computing, Parallel Computing, and HPCC 13. References 14. Other Books You May Enjoy

Testing Python

The steps for testing Python are as follows:

  1. For PC users, after clicking All Programs, Anaconda3.6, and then Anaconda Prompt, we would see the following.

Note that different users would probably get a different path:

  1. Then, just type python, and we can launch it, as shown here:
  1. It tells us that Python 3.6.3 was operational. We could also try import scipy as sp to see if it is preinstalled:
  1. After we type import scipy as sp, no error message appears, which indicates that the package was preinstalled. The command of sp.sqrt(3) would offer us the square root of 3. Another example with the related graph is shown here:
import scipy as np 
from pylab import * 
x=np.linspace(-np.pi,np.pi,256,endpoint=True) 
c,s=np.cos(x),np.sin(x) 
plot(x,c),plot(x,s) 
show()  

The previous code will give an output such as the following:

...
You have been reading a chapter from
Hands-On Data Science with Anaconda
Published in: May 2018
Publisher: Packt
ISBN-13: 9781788831192
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