March 2017
Intermediate to advanced
328 pages
11h 21m
English
Content preview from Think Like a Data ScientistBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Chapter 4. Data wrangling: from capture to domestication
This chapter covers
- Ways to wrangle data
- Helpful tools and techniques
- Some common pitfalls
One definition of wrangling is “having a long and complicated dispute.” That sounds about right.
Data wrangling is the process of taking data and information in difficult, unstructured, or otherwise arbitrary formats and converting it into something that conventional software can use. Like many aspects of data science, it’s not so much a process as it is a collection of strategies and techniques that can be applied within the context of an overall project strategy. Wrangling isn’t a task with steps that can be prescribed exactly beforehand. Every case is different and takes some problem solving ...
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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.