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Data Science with SQL Server Quick Start Guide

You're reading from   Data Science with SQL Server Quick Start Guide Integrate SQL Server with data science

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781789537123
Length 206 pages
Edition 1st Edition
Languages
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Author (1):
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Dejan Sarka Dejan Sarka
Author Profile Icon Dejan Sarka
Dejan Sarka
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Table of Contents (10) Chapters Close

Preface 1. Writing Queries with T-SQL FREE CHAPTER 2. Introducing R 3. Getting Familiar with Python 4. Data Overview 5. Data Preparation 6. Intermediate Statistics and Graphs 7. Unsupervised Machine Learning 8. Supervised Machine Learning 9. Other Books You May Enjoy

Creating dummies


Some algorithms, for example, regression analysis algorithms, need numerical input variables. If you want to use a categorical variable in the analysis, you need to convert it somehow to a numerical one. If the variable is ordinal, this is not a problem; you just assign appropriate integers to the naturally ordered values of the variable. From a nominal variable, you can create a set of indicators. There is one indicator for each possible value, showing whether the value it represents is taken for a case. If a specific value is taken for a case, you assign 1 to the indicator for this value value, or otherwise 0. Such new variables, the indicators, are also called dummy variables, or dummies. In T-SQL, you can use the IIF() function to generate dummies, as the following code shows:

SELECT TOP 3 MaritalStatus,
 IIF(MaritalStatus = 'S', 1, 0)
 AS [TM_S],
 IIF(MaritalStatus = 'M', 1, 0)
 AS [TM_M]
FROM dbo.vTargetMail;

 

 

 

Here are the results:

MaritalStatus TM_S        TM_M
--...
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