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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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Toc

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

Finding environmental variables

For R, we can use the Sys.getenv() function to find all environmental variables:

To save space, only the top part is shown. Again, different users will get different results. For Python, we use the following commands:

import sys
sys.path

The top part of the output is shown here:

For Julia, we use the ENV function, as in the following:

For Octave, we can use the getenv() function, as shown:

>> getenv('path') 
ans = C:OctaveOctave-4.0.0bin;C:Program FilesSilverfrostFTN95;C:Perlsitebin;C:Perlbin;C:windowssystem32;C:windows;C: 
windowsSystem32Wbem;C:windowsSystem32WindowsPowerShellv1.0;C:Program FilesIntelOpenCL SDK2.0binx86;C:Program Files 
Common FilesRoxio SharedDLLShared;C:Program FilesCommon FilesRoxio Shared10.0DLLShared;C:Program FilesMATLABR2013abin 
;C:Anaconda;C:AnacondaScripts;C:Program FilesWindows Kits8.1Windows Performance...
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