July 2017
Beginner to intermediate
715 pages
17h 3m
English
Content preview from Java: Data Science Made Easy
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Summary
Many times, half the battle in data science is manipulating data so that it is clean enough to work with. In this chapter, we examined many techniques for taking real-world, messy data and transforming it into workable datasets. This process is generally known as data cleaning, wrangling, reshaping, or munging. Our focus was on core Java techniques, but we also examined third-party libraries.
Before we can clean data, we need to have a solid understanding of the format of our data. We discussed CSV data, spreadsheets, PDF, and JSON file types, as well as provided several examples of manipulating text file data. As we examined text data, we looked at multiple approaches for processing the data, including tokenizers, Scanners, and ...
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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.