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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 showed you how to install Anaconda and test if the installation was successful. We looked at how to launch Jupyter and how to use it to launch Python, how to launch Spyder and R, and how to find help. Most of these concepts or procedures are quite basic, so users who are quite confident with them can skip this chapter and go to Chapter 3, Data Basics, directly.

In Chapter 3, Data Basics, we first discuss open data sources such as the UCI (University of California at Irvin) machine learning depository and the bureau of labor statistics. Then, we introduce the Python Pandas package. Many issues, such as how to deal with missing data, sorting, how to slice and dice datasets, merging different datasets, and data input and output, will be discussed in detail. Several relevant packages for data manipulation will be also introduced and discussed.

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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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