Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
SQL Server 2016 Developer's Guide

You're reading from   SQL Server 2016 Developer's Guide Build efficient database applications for your organization with SQL Server 2016

Arrow left icon
Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781786465344
Length 616 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Dejan Sarka Dejan Sarka
Author Profile Icon Dejan Sarka
Dejan Sarka
Miloš Radivojević Miloš Radivojević
Author Profile Icon Miloš Radivojević
Miloš Radivojević
William Durkin William Durkin
Author Profile Icon William Durkin
William Durkin
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Introduction to SQL Server 2016 FREE CHAPTER 2. Review of SQL Server Features for Developers 3. SQL Server Tools 4. Transact-SQL Enhancements 5. JSON Support in SQL Server 6. Stretch Database 7. Temporal Tables 8. Tightening the Security 9. Query Store 10. Columnstore Indexes 11. Introducing SQL Server In-Memory OLTP 12. In-Memory OLTP Improvements in SQL Server 2016 13. Supporting R in SQL Server 14. Data Exploration and Predictive Modeling with R in SQL Server

Manipulating data

Before you can extract some information from your data, you need to understand how the data is stored. First, you need to understand data structures in R.

Scalars and vectors are the most basic data structures. In R terminology, you analyze a dataset. A dataset consists of rows with cases or observations to analyze and columns representing the variables or attributes of the cases. This definition of a dataset looks like a SQL Server table. However, R does not work with tables in the relational sense. For example, in a relational, the order of rows and columns is not defined. In order to get a value, you need the column name and the key of the row. However, in R, you can use the position of a cell for most of the data structures. You have already seen this position reference for vectors.

In this section, you will learn about the data structures in R and the basic manipulation of datasets, including:

  • Arrays and matrices
  • Factors
  • Data frames
  • Lists
  • Creating new variables
  • Recoding variables...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image