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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

Summary

In this chapter, we first discussed sources of open data, which included The Bureau of Labor Statistics, the Census Bureau, Professor French's data library, the Federal Reserve's data library, and the UCI Machine Learning Depository. After that, we showed you how to input data; how to deal with missing data; how to sort, slice, and dice the datasets; and how to merge different datasets. Data output was discussed in detail. For different languages, such as Python, R, and Julia, several relevant packages for data manipulation were introduced and discussed.

In Chapter 4, Data Visualization, we will discuss data visualization in R, Python, and Julia separately. To make our visual presentation more eye catching, we will show how you to generate simple graphs and bar charts, as well as how to add trend lines and legends. Other explanations will include how to save...

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