July 2018
Beginner to intermediate
146 pages
3h 39m
English
Content preview from Hands-On Recommendation Systems with Python
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Manipulating Data with the Pandas Library
In the next few portions of the book, we are going to get our hands dirty by building the various kinds of recommender systems that were introduced in chapter one. However, before we do so, it is important that we know how to handle, manipulate, and analyze data efficiently in Python.
The datasets we'll be working with will be several megabytes in size. Historically, Python has never been well-known for its speed of execution. Therefore, analyzing such huge amounts of data using vanilla Python and the built-in data structures it provides us is simply impossible.
In this chapter, we're going to get ourselves acquainted with the pandas library, which aims to overcome the aforementioned limitations, ...
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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.