Lecture Notes: Information Processing in R

The R Programming Language

The R programming language is one of the most commonly used languages for ad hoc data analysis in business when Excel is not sufficient or not able to handle large data sets.​ It is also often used to develop data mining or machine learning solutions, although production code is often re-written in Java or C++.

Programming with R

Environments:
Variables & Identifiers:
  • Variables hold values: scalars, text strings, data frames, results from calls to functions
  • Variables have names that must follow certain rules: must start with a letter, can contain letters digits and certain special characters including dot (.) and underscore (_)
  • The dot (.) as a regular character can be confusing as other language (e.g., Java) use dot to designate property or method access 
  • Legal Variable Names:
    • df
    • df2
    • df.txns
    • df_all2017
  • Illegal Variable Names:
    • 2df           -- cannot start with a digit
    • rs$all        -- cannot contain a $; the $ is used to access columns in a dataframe
    • rs#           -- only . and _ are allowed in addition to digits and letters
Data & Object Types:
  • Variables are typed in R based on what value they contain:
  • The types can change simply by assigning a new value
  • Types can be converted using as.xxxx functions, e.g., as.numeric or as.date or as.string
  • Conversions are often necessary when data is read from CSV or XML files or databases
Variables, Objects, Assignment

    









Data Frames



Data frames are essentially spreadsheets; they are tables of rows and columns where each row is a data case and each column is a value.




	

    

        
Working with Data Frames

    

    

        

    









Loading Data from Files



Data Sets for code below:




	

    

        
Load Data from CSV into Dataframe

    

    

        

    









Queries on Data Frames




	

    

        
Queries on Data Frames

    

    

        

    










	

    

        
Dealing with Missing Data Values

    

    

        

    









Loading Data from Database into Data Frame with SQL



Data Sets & SQLite database for code below:




	

    

        
Database Queries in R

    

    

        

    









Loading XML File into R



  • requires the library XML, so after installing the library from CRAN, use the command library(XML)




	

    

        
Processing XML in R via XPath

    

    

        

    










	

    

        
Processing XML in R via Tree

    

    

        

    










	

    

        
Processing XML in R via XPath