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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

Data Basics

In this chapter, we'll first discuss sources of open data, which includes the University of California at Irvine (UCI) Machine Learning Depository, the Bureau of Labor Statistics, the Census Bureau, Professor French's Data Library, and the Federal Reserve's Data Library. Then, we will show you several ways of inputting data, how to deal with missing values, sorting, choosing a subset, merging different datasets, and data output. For different languages, such as Python, R, and Julia, several relevant packages for data manipulation will be introduced as well. In particular, the Python pandas package will be discussed.

In this chapter, the following topics will be covered:

  • Sources of data
  • Introduction to the Python pandas package
  • Several ways to inputting packages
  • Introduction to the Quandl data delivery platform
  • Dealing with missing data
  • Sorting data...
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