May 2018
Beginner to intermediate
364 pages
7h 43m
English
Content preview from Hands-On Data Science with Anaconda
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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 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.