switch Statement in R

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In R language, the switch statements allow a variable to be tested for equality against a list of values. Each value in a list is called a case, and the variable being switched on is checked for each case. R switch is almost the same as the if statement regarding working functionality.

The basic syntax is

Basic Syntax of Switch Statement in R Language

switch(expression,
     case 1,
     case 2,
     case 3,
     .
     .
)

The expression values are tested against multiple cases (case1, case2, …, casen). The one-line syntax is,

switch statement in r

An R Language Switch statement allows a default statement can also be added. The default statement will be executed when the Expression value is not matching with any of the case statements.

The following example is a simple command-line type calculator using R.

Simple Calculator Example

number1  <- 30
number2  <- 20
operator <- readline(prompt = "Enter any ARITHMETIC OPERATOR (+, -, *, ^, /, %/%, %%)!: ")

switch(operator,
       "+" = print(paste("Addition (number1+number2) = ", number1 + number2)),
       "-" = print(paste("Subtraction (number1-number2) = ", number1 - number2)),
       "*" = print(paste("Multiplication (number1*number2) = ", number1 * number2)),
       "^" = print(paste("Exponent (number1^number2) = ", number1 ^ number2)),
       "/" = print(paste("Division (number1/number2) = ", number1 / number2)),
       "%/%" = print(paste("Integer Division (number1 %/% number2) = ", number1 %/% number2)),
       "%%" = print(paste("Division (number1 %% number2) = ", number1 %% number2))
)

From the above example, one can easily compute some basic computations on two numbers. The operation on these two numbers depends on the input given to readline( ) the function and the expression in the switch. The operator value from readline() is matched with the options (cases) in the switch statement and results are displayed when matched.

Probability under the F-Curve

Consider another example, for different probabilities, the area under the curve for an F-curve can be selected using the switch as given below.

# q contains the probability under the curve for a F-curve
q <- c(0.25, 0.5, 0.75, 0.999)
test = 3
v1 = 10
v2 = 20

switch(test,
      "1" = print (qf(q[1], df1=v1, df2=v2, lower.tail = T) ),
      "2" = print (qf(q[2], df1=v1, df2=v2, lower.tail = T) ),
      "3" = print (qf(q[3], df1=v1, df2=v2, lower.tail = T) ),
      "4" = print (qf(q[4], df1=v1, df2=v2, lower.tail = T) )
)

The code above will produce F-table values for different probability values.

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if Statement in R: if-else, if-else-if Conditional Statement

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General Introduction to if Statement in R

In R Language, the if statement(s) is a conditional control used for making a decision. The if statement in R is used to run the block of statements when a certain condition is met. Therefore, if statements are also called conditional statements.

if Statement in R

An if statement consists of a boolean expression followed by one or more statements. The basic syntax for creating a if statement is

if ( boolean expression ) {
      # statements 
      # these statements will execute only if the boolean expression is true
}

The code inside the brackets of the if statement will be executed if the boolean expression in parenthesis evaluates to be true. For example,

x <- 3.0L
if ( is.integer(x) ){
   print("x is an integer")
}

if-else Statement

An if statement can be followed by an optional else statement. The else statement executes only when the boolean expression in the parenthesis of the if statement evaluates to false. The basic syntax of a if-else statement is

if (boolean expression){
        # statement(s) will execute if the boolean expression is true 
}
else{
      # statemenet(s) will execute if boolean expression is false
}
if statement in R syntax

For example,

x <- 31
if ( x %% 2 == 0 ){
   print("X is even")
}else{
  print("X is odd")
}
if Statement in R

if-else-if Statement

An if statement can be followed by an optional else-if-else statement, which is very useful for testing various conditions using a single if-else-if statement. The basic syntax for creating an if-else-if is

if ( boolean expression-1 ){
      # statements execute when the boolean expression-1 is true
} else if ( boolean expression-2 ) {
     # statements execute when the boolean expression-2 is true
} else if ( boolean expression-3 ){
    # statements execute when the boolean expression-3 is true
} else {
    # statements execute when none of the above condition is true
}

For example,

# Consider durbin watson statistics
d = -2
if (d == 2){
   print("no autocorrelation")
} else if (d > 0 &amp; d &lt; 2){
   print("Positive autocorrelation")
} else if (d > 2){
   print("successive error terms are negatively correlated")
} else {
  print("d is less than 0")
}

The value of $d (d=-2)$ will be compared with the expression’s result in the parenthesis of if or else if statement. From all of the if or else if statements only one statement will be true. In the example, $d=-2$ does not match with any of the if (or else if statement), therefore, the last statement (that is else statement) will be executed.

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Import Data Files Into R Language

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You can read/import data files into R that are produced by different software such as MS Excel, Minitab, SPSS, SAS, and STATA.

Import Data Files into R Language

In R language different data file formats can be read or imported easily. Let us start learning about how to import Data Files into R Language such as Excel, SPSS, STATA, SAS, Minitab, etc format.

Reading Excel Files in R

The XLConnect package can be used to import data files into R produced in MS Excel. First, you have to install this package.

install.packages("XLConnect")

You can check if the package is already installed using the code:

any(grepl("XLConnect", installed.packages()))

If the package is installed, you need to activate the package in your workspace (using library( ) function) to load data from MS Excel files.

importing Data Files into R Language

Suppose, you have a data file (Hald.xlsx) stored at the path "D:\STAT\STA-654\Hald.xlsx". To read this file the readWorksheetFromFile( ) function can be used. For example,

library(XLConnect) 
data &lt;- readWorksheetFromFile("D:/stat/sta-654/Hald.xlsx", sheet=1)

Since an Excel workbook can contain more than one sheet, therefore, you need to specify the sheet argument and specify which sheet you want to load into R. In this example, data from sheet 1 will be loaded.

If you want to load the whole workbook (all sheets) use the loadWorkbook( ) function to load the required worksheet as a data file frame. For example,

wb <- loadWorkbook("D:/stat/sta-654/Hald.xlsx") 
df <- readWorksheet(wb, sheet = 1)

The readxl package can also be used to read MS Excel files more easily.

library(readxl) 
df <- read_excel("Data file with path")

Note that the MS Excel files with extension: *.xls, or *.xlsx can be specified. The sheet argument can also be added, just like with the XLSconnect package.

Read SPSS Data Files

To read the SPSS files install foreign package. After loading the foreign package, the read.spss( ) function can be used to load an SPSS data file in R. For example,

library(foreign) 
mydata &lt;- read.spss ("SPSS data file with path", to.data.frame = TRUE)

The argument to.data.frame is set to TRUE so that the data is displayed in a data frame format. Since the SPSS data file contains value labels, and if you do not want the variables with value labels to be converted into R factors with corresponding levels, setuse.value.labels = FALSE. For example,

library(foreign) 

mydata <- read.spss("SPSS data file with path", 
                    to.data.frame = TRUE, 
                    use.value.labels = FALSE)

Reading STATA Data Files

To import Stata files the read.dta( ) function from the foreign package can be used. For example,

library(foreign) 
mydata &lt;- read.dta("STATA file with path")

Reading SAS Data Files

The read.sas7bdat( ) function from sas7bdat package can be used to read SAS data files into R.

library(sas7bdat) 
mydata &lt;- read.sas7bdat("SAS data file with path")

Reading Minitab Data File

Minitab data files can be imported in R using read.mtp( ) function from foreign package.

library(foreign) 
mydata &lt;- read.mtp("Minitab data file with path")

Reading RDA or RData Files

The R data files RDA and RData files can be easily read using load( ) function.

load("filename.RDA")

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