A brief summary of reading structured data into R.

1. Reading Structured Data into R
Srikanth Potukuchi
Analytics Consultant
srikanth.potukuchi@gmail.com
April 21, 2018
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2. Overview
1 Introduction
2 Delimited Files
3 Excel Files
4 Reading from Database
5 Data from Other Statistical Tools
6 Getting Website Data
7 Summary
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3. Introduction
Introduction-Focus on Structured Data
Data comes in many forms: Structured and UnStructured. In this
deck, we are focusssing on Structured Data-which is basically in the form
of rows and columns (Also known as Tabular Data).
We will look at reading delimited files(CSV, Tab, Special
delimiters), excel files, database(MS Access and Oracle), data from other
Statistical tools like SAS, SPSS, Stata, Octave, Minitab,and Systat; and
finally we will look at extracting data from Websites as well.
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4. Introduction
Introduction-Installing Packages
Installing a package in R can be done using install.packages(“Your
Package Name”) and except for the built-in Base package- other packages
have to be loaded using library(Your Package Name) or require(Your
Package Name). Here’s an example:
>install.packages(‘‘RODBC ’’)
>library(RODBC)
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5. Introduction
Data Included with R.
Suppose we install a package- say ggplot2.
What datasets are included in this package?
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6. Delimited Files
Delimited Files-Comma Separated File (CSV)
CSV files are mostly read using read.csv() or read.csv2(). The
difference between the two is the default separator and decimal point. The
basic syntax is:
>read.csv(file ,header=TRUE , sep=",",quote=""",
dec=".",fill=TRUE ,comment.char="" ,...)
>read.csv2(file ,header=TRUE ,sep=";",quote=""",
dec=",",fill=TRUE ,comment.char="" ,...)
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7. Delimited Files
Delimited Files-Comma Separated File (CSV)
Large CSV files are mostly read using read.table(). The basic
syntax is:
>read.table(file ,header=FALSE , sep="",quote=""",
dec=".",stringsAsFactors =default. stringsAsFactors () ,...)
Reading CSV file from a website
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8. Delimited Files
Delimited Files-Comma Separated File (CSV)
The result of using read.table is a data.frame. The path will give an
error if forward slash or double slash is not used.
Reading CSV file locally
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9. Excel Files
Excel Files
Difficult to read excel data into R
Simplest method convert the Excel file to a CSV file.
Packages to address this problem:
Gdata
XLConnect
xlsReadWrite
Reading Excel file locally-set the path
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10. Excel Files
Excel Files
Use the function readWorksheetFromFile
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11. Reading from Database
Reading from Database
To read from databases like Microsoft SQL Server,DB2, MySQL,
Oracle SQL or Microsoft Access we must provide an ODBC
connection.
We need RODBC package to use ODBC in R.
First Step is to create a DSN which differs by OS.
ODBC Connection
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12. Reading from Database
Reading from Database
Download necessary drivers if not present here:
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13. Reading from Database
Reading from MS Access Database
Add the data source:
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14. Reading from Database
Reading from MS Access Database
Use odbcConnect() function:
Use sqlQuery() function:
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15. Reading from Database
Reading from Oracle Database
Use this Link for details on reading from Oracle Database.:
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16. Data from Other Statistical Tools
Data from Other Statistical Tools
List of Packages and Functions:
Reading fromSystat:
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17. Getting Website Data
Simple HTML Tables
Use XML package:
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18. Getting Website Data
Simple HTML Tables
Use readHTMLTable function:
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19. Getting Website Data
Use Regular Expressions to scrape the Web.
Presidents Data:
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20. Getting Website Data
Use Regular Expressions to scrape the Web.
Use stringr package: Here we used str split() to split a column based on a
pattern.
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21. Getting Website Data
Use Regular Expressions to scrape the Web.
Use Reduce() to combine the rows into a Matrix.
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22. Getting Website Data
Use Regular Expressions to scrape the Web.
Final Results.
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23. Summary
Packages and Functions
Data Packages Functions
CSV Base read.csv(),read.csv2(), read.table()
Excel XLConnect readWorksheetFromFile()
Database RODBC odbcConnect()
SAS sas7bdat read.sas7bdat()
All other foreign read.spss(), read.dta(), read.octave()
read.mtp(),read.sysstat()
Table : R Packages for reading Structured Data
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24. Summary
Use files across platforms- Windows,Mac,and Linux OS.
Use Rdata files to pass around data or any R objects like variables and
functions.
Use Save().
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25. Summary
References
Jared P. Lander (2013)
R for Everyone: Advanced Analytics and Graphics
Addison-Wesley Data & Analytics Series.
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