for loop

for loops iterate over elements of a looping vector.

Syntax

for(variable in sequence) { 
	statements 
}

Example

mydf <- iris
myve <- NULL
for(i in seq(along=mydf[,1])) {
	myve <- c(myve, mean(as.numeric(mydf[i,1:3])))
}
myve[1:8]
## [1] 3.333333 3.100000 3.066667 3.066667 3.333333 3.666667 3.133333 3.300000

Note: Inject into objecs is much faster than append approach with c, cbind, etc.

Example

myve <- numeric(length(mydf[,1]))
for(i in seq(along=myve)) {
	myve[i] <- mean(as.numeric(mydf[i,1:3]))
}
myve[1:8]
## [1] 3.333333 3.100000 3.066667 3.066667 3.333333 3.666667 3.133333 3.300000

Conditional Stop of Loops

The stop function can be used to break out of a loop (or a function) when a condition becomes TRUE. In addition, an error message will be printed.

Example

x <- 1:10
z <- NULL
for(i in seq(along=x)) { 
	if(x[i] < 5) { 
		z <- c(z, x[i]-1)  
	} else { 
		stop("values need to be < 5") 
	}
}

while loop

Iterates as long as a condition is true.

Syntax

while(condition) {
	statements
}

Example

z <- 0
while(z<5) { 
	z <- z + 2
	print(z)  
}
## [1] 2
## [1] 4
## [1] 6

The apply Function Family

apply

Syntax

apply(X, MARGIN, FUN, ARGs)

Arguments

  • X: array, matrix or data.frame
  • MARGIN: 1 for rows, 2 for columns
  • FUN: one or more functions
  • ARGs: possible arguments for functions

Example

apply(iris[1:8,1:3], 1, mean)
##        1        2        3        4        5        6        7        8 
## 3.333333 3.100000 3.066667 3.066667 3.333333 3.666667 3.133333 3.300000

tapply

Applies a function to vector components that are defined by a factor.

Syntax

tapply(vector, factor, FUN)

Example

iris[1:2,]
##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
tapply(iris$Sepal.Length, iris$Species, mean)
##     setosa versicolor  virginica 
##      5.006      5.936      6.588

sapply and lapply

Both apply a function to vector or list objects. The lapply function always returns a list object, while sapply returns vector or matrix objects when it is possible.

Examples

x <- list(a = 1:10, beta = exp(-3:3), logic = c(TRUE,FALSE,FALSE,TRUE))
lapply(x, mean)
## $a
## [1] 5.5
## 
## $beta
## [1] 4.535125
## 
## $logic
## [1] 0.5
sapply(x, mean)
##        a     beta    logic 
## 5.500000 4.535125 0.500000

Often used in combination with a function definition:

lapply(names(x), function(x) mean(x))
sapply(names(x), function(x) mean(x))



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