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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

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781786465344
Length 616 pages
Edition 1st Edition
Languages
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Authors (3):
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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
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Toc

Table of Contents (15) Chapters Close

Preface 1. Introduction to SQL Server 2016 2. Review of SQL Server Features for Developers FREE CHAPTER 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...
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