April 2024
Beginner
832 pages
20h 32m
English
book
Data Analytics & Visualization All-in-One For Dummies
by Jack A. Hyman, Luca Massaron, Paul McFedries, John Paul Mueller, Lillian Pierson, Jonathan Reichental, Joseph Schmuller, Alan R. Simon, Allen G. Taylor
Content preview from Data Analytics & Visualization All-in-One For Dummies
Become 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,
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.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.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.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.
Chapter 1
Using Open Source R for Data Science
IN THIS CHAPTER
Exploring R programming
Previewing popular R packages
Playing with more advanced R packages
Data science involves the skillful application of math, coding, and subject matter expertise in ways that allow data scientists to generate reliable and accurate predictions from data. While the last element — subject matter expertise — is unique to each practitioner, if you apply data science within a business context, then you’d want to make sure you’ve got a good handle on the needed business acumen and the math-and-statistics requirements of data science (Book 1, Chapter 3). Another important data science constituent to consider is coding, which can be done using the open source programming language R, as covered in this chapter, or Python (covered in Book 6).
This chapter describes the fundamental concepts of programming with R (such as data types, functions, and classes). The machine learning models you build with R or Python can serve as the decision engines within AI SaaS products you build for your company. The chapter also introduces some of the best R packages for manipulating data, performing statistical computations, ...
Become 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,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
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.