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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

Organizing the data

I want to start this section by showing you some of Python's analytical and graphic capabilities. I am explaining the code just briefly here; you will learn more about Python data structures very quickly. Let's start coding! First, I need to import the necessary libraries:

import numpy as np
import pandas as pd
import pyodbc
import matplotlib.pyplot as plt

For the data I will analyze, I am using the data from the AdventureWorksDW2017 demo database, selecting from the dbo.vTargetMail view, like I did in Chapter 2, Introducing R, when I introduced the R language. I am also using ODBC to connect to SQL Server, with the same data source name and SQL Server login as I did then:

con = pyodbc.connect('DSN=AWDW;UID=RUser;PWD=Pa$$w0rd')
query = """SELECT CustomerKey,
Age, YearlyIncome,
CommuteDistance, BikeBuyer...
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