June 2021
Beginner to intermediate
196 pages
5h 1m
English
Content preview from Python and R for the Modern Data Scientist
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Chapter 4. Data Format Context
In this chapter we’ll review tools in Python and R for importing and processing data in a variety of formats. We’ll cover a selection of packages, compare and contrast them, and highlight the properties that make them effective. At the end of this tour, you’ll be able to select packages with confidence. Each section illustrates the tool’s capabilities with a specific mini case study, based on tasks that a data scientist encounters daily. If you’re transitioning your work from one language to another or simply want to find out how to get started quickly using complete, well-maintained, and context-specific packages, this chapter will guide you.
Before we dive in, remember that the open source ecosystem is constantly changing. New developments, such as transformer models and explainable artificial intelligence (XAI), seem to emerge every other week. These often aim at lowering the learning curve and increasing developer productivity. This explosion of diversity also applies to related packages, resulting in a nearly constant flow of new and (hopefully) better tools. If you have a very specific problem, there’s probably a package already available for you, so you don’t have to reinvent the wheel. Tool selection can be overwhelming, but at the same time this variety of options can improve the quality and speed of your data science work.
The package selection in this chapter can appear limited in view; hence, it is essential to clarify our ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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.