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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

Using Python via Jupyter

Here, we show you how to write simple Python code via Jupyter:

  1. From the menu, after clicking Anaconda, we can find an entry called Jupyter Notebook. After clicking on that entry, we can see the following:
  1. If we click New on the right-hand side, we can find several choices. After we choose Python 3, we end up with the following starting file:
  1. We can now type our Python commands in the box. Remember to press Shift + Enter if you want to execute the command (shown here):
  1. We can also type multiple commands and execute them, as shown here:

The colorful and distinct treatment of keywords, parentheses, and values makes our programming a little easier.

We could save our programs by choosing File|Save and Checkpoint on the menu bar. Similarly, we could load our presaved programs by choosing File|Revert to Checkpoint directly from the menu bar or finding...
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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