May 2018
Beginner to intermediate
364 pages
7h 43m
English
Content preview from Hands-On Data Science with Anaconda
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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 ...
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I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.