What do we want to be able to do?

The course provides a brief overview of R data structures followed by the following topics:

  • Loops in R

  • Vectorized functions (apply family of functions)

  • How R functions work

  • Function writing

Writing Functions

  • Knowing how to write functions vital to custom analyses!

  • Function writing syntax

nameOfFunction <- function(input1, input2, ...) {
  #code
  #return something with return()
  #or returns last value
}

Writing Functions

  • Can look at code for functions
var
## function (x, y = NULL, na.rm = FALSE, use) 
## {
##     if (missing(use)) 
##         use <- if (na.rm) 
##             "na.or.complete"
##         else "everything"
##     na.method <- pmatch(use, c("all.obs", "complete.obs", "pairwise.complete.obs", 
##         "everything", "na.or.complete"))
##     if (is.na(na.method)) 
##         stop("invalid 'use' argument")
##     if (is.data.frame(x)) 
##         x <- as.matrix(x)
##     else stopifnot(is.atomic(x))
##     if (is.data.frame(y)) 
##         y <- as.matrix(y)
##     else stopifnot(is.atomic(y))
##     .Call(C_cov, x, y, na.method, FALSE)
## }
## <bytecode: 0x0000000019558700>
## <environment: namespace:stats>

Writing Functions

  • Can look at code for functions
colMeans
## function (x, na.rm = FALSE, dims = 1L) 
## {
##     if (is.data.frame(x)) 
##         x <- as.matrix(x)
##     if (!is.array(x) || length(dn <- dim(x)) < 2L) 
##         stop("'x' must be an array of at least two dimensions")
##     if (dims < 1L || dims > length(dn) - 1L) 
##         stop("invalid 'dims'")
##     n <- prod(dn[id <- seq_len(dims)])
##     dn <- dn[-id]
##     z <- if (is.complex(x)) 
##         .Internal(colMeans(Re(x), n, prod(dn), na.rm)) + (0+1i) * 
##             .Internal(colMeans(Im(x), n, prod(dn), na.rm))
##     else .Internal(colMeans(x, n, prod(dn), na.rm))
##     if (length(dn) > 1L) {
##         dim(z) <- dn
##         dimnames(z) <- dimnames(x)[-id]
##     }
##     else names(z) <- dimnames(x)[[dims + 1L]]
##     z
## }
## <bytecode: 0x0000000018fe4f28>
## <environment: namespace:base>

Writing Functions

  • Can look at code for functions
mean
## function (x, ...) 
## UseMethod("mean")
## <bytecode: 0x0000000017e89428>
## <environment: namespace:base>

Writing Functions

  • Can look at code for functions
mean.default
## function (x, trim = 0, na.rm = FALSE, ...) 
## {
##     if (!is.numeric(x) && !is.complex(x) && !is.logical(x)) {
##         warning("argument is not numeric or logical: returning NA")
##         return(NA_real_)
##     }
##     if (na.rm) 
##         x <- x[!is.na(x)]
##     if (!is.numeric(trim) || length(trim) != 1L) 
##         stop("'trim' must be numeric of length one")
##     n <- length(x)
##     if (trim > 0 && n) {
##         if (is.complex(x)) 
##             stop("trimmed means are not defined for complex data")
##         if (anyNA(x)) 
##             return(NA_real_)
##         if (trim >= 0.5) 
##             return(stats::median(x, na.rm = FALSE))
##         lo <- floor(n * trim) + 1
##         hi <- n + 1 - lo
##         x <- sort.int(x, partial = unique(c(lo, hi)))[lo:hi]
##     }
##     .Internal(mean(x))
## }
## <bytecode: 0x0000000014e129e8>
## <environment: namespace:base>

Writing Functions

  • Goal: Create a standardize() function

  • Take vector of values

    • subtract mean
    • divide by standard deviation

  • z-score idea

  • Formula: For value i,
    \[\frac{(value[i]-mean(value))}{sd(value)}\]

Writing Functions

nameOfFunction <- function(input1, input2, ...) {
  #code
  #return something with return()
  #or returns last value
}
standardize <- function(vector) {
    return((vector - mean(vector)) / sd(vector))
}

Writing Functions

  • Now use it!
data <- runif(5)
data
## [1] 0.1985510 0.9055358 0.1268306 0.4333906 0.1967265
result <- standardize(data)
result
## [1] -0.5428453  1.6671771 -0.7670422  0.1912591 -0.5485487

Writing Functions

  • Check result has mean 0 and sd 1
mean(result)
## [1] 2.218278e-17
sd(result)
## [1] 1

Writing Functions

  • Goal: Add more inputs
  • Make centering optional
  • Make scaling optional
standardize <- function(vector, center, scale) {
    if (center) {
        vector <- vector - mean(vector)
    }
    if (scale) {
        vector <- vector / sd(vector)
    }
    return(vector)
}

Writing Functions

result <- standardize(data, center = TRUE, scale = TRUE)
result
## [1] -0.5428453  1.6671771 -0.7670422  0.1912591 -0.5485487
result <- standardize(data, center = FALSE, scale = TRUE)
result
## [1] 0.6206673 2.8306897 0.3964704 1.3547717 0.6149638

Writing Functions

  • Give center and scale default arguments
standardize <- function(vector, center = TRUE, scale = TRUE) {
    if (center) {
        vector <- vector - mean(vector)
    }
    if (scale) {
        vector <- vector / sd(vector)
    }
    return(vector)
}

Writing Functions

result <- standardize(data, center = TRUE, scale = TRUE)
result
## [1] -0.5428453  1.6671771 -0.7670422  0.1912591 -0.5485487
result <- standardize(data)
result
## [1] -0.5428453  1.6671771 -0.7670422  0.1912591 -0.5485487

Writing Functions

  • Return more than 1 object by returning a list

  • Goal: Also return

    • mean() of original data
    • sd() of original data

Writing Functions

standardize <- function(vector, center = TRUE, scale = TRUE) {
    mean <- mean(vector)
    stdev <- sd(vector)
    if (center) {
        vector <- vector - mean
    }
    if (scale) {
        vector <- vector / stdev
    }
    return(list(vector, mean, stdev))
}

Writing Functions

result <- standardize(data)
result  
## [[1]]
## [1] -0.5428453  1.6671771 -0.7670422  0.1912591 -0.5485487
## 
## [[2]]
## [1] 0.3722069
## 
## [[3]]
## [1] 0.3198993
result[[2]]
## [1] 0.3722069

Writing Functions

  • Fancy up what we return by giving names
standardize <- function(vector, center = TRUE, scale = TRUE) {
    mean <- mean(vector)
    stdev <- sd(vector)
    if (center) {
        vector <- vector - mean
    }
    if (scale) {
        vector <- vector / stdev
    }
    return(list(result = vector, mean = mean, sd = stdev))
}

Writing Functions

result <- standardize(data, center = TRUE, scale = TRUE)
result  
## $result
## [1] -0.5428453  1.6671771 -0.7670422  0.1912591 -0.5485487
## 
## $mean
## [1] 0.3722069
## 
## $sd
## [1] 0.3198993
result$sd
## [1] 0.3198993

Quick Examples

Writing Functions

  • Can bring in unnamed arguments
  • Arguments that can be used by functions inside your function
mean
## function (x, ...) 
## UseMethod("mean")
## <bytecode: 0x0000000017e89428>
## <environment: namespace:base>
x <- c(rnorm(5), NA)
mean(x)
## [1] NA
mean(x, na.rm = TRUE)
## [1] 0.4093447

Writing Functions

  • Can bring in unnamed arguments
  • Arguments that can be used by functions inside your function
plot
## function (x, y, ...) 
## UseMethod("plot")
## <bytecode: 0x00000000161dd960>
## <environment: namespace:graphics>
plot(x = 1:5, y = (1:5)^2, type = "l", lty = "dashed")

Writing Functions

plot(x = 1:5, y = (1:5)^2, type = "l", lty = "dashed")

Writing Functions

plot.default
## function (x, y = NULL, type = "p", xlim = NULL, ylim = NULL, 
##     log = "", main = NULL, sub = NULL, xlab = NULL, ylab = NULL, 
##     ann = par("ann"), axes = TRUE, frame.plot = axes, panel.first = NULL, 
##     panel.last = NULL, asp = NA, xgap.axis = NA, ygap.axis = NA, 
##     ...) 
## {
##     localAxis <- function(..., col, bg, pch, cex, lty, lwd) Axis(...)
##     localBox <- function(..., col, bg, pch, cex, lty, lwd) box(...)
##     localWindow <- function(..., col, bg, pch, cex, lty, lwd) plot.window(...)
##     localTitle <- function(..., col, bg, pch, cex, lty, lwd) title(...)
##     xlabel <- if (!missing(x)) 
##         deparse(substitute(x))
##     ylabel <- if (!missing(y)) 
##         deparse(substitute(y))
##     xy <- xy.coords(x, y, xlabel, ylabel, log)
##     xlab <- if (is.null(xlab)) 
##         xy$xlab
##     else xlab
##     ylab <- if (is.null(ylab)) 
##         xy$ylab
##     else ylab
##     xlim <- if (is.null(xlim)) 
##         range(xy$x[is.finite(xy$x)])
##     else xlim
##     ylim <- if (is.null(ylim)) 
##         range(xy$y[is.finite(xy$y)])
##     else ylim
##     dev.hold()
##     on.exit(dev.flush())
##     plot.new()
##     localWindow(xlim, ylim, log, asp, ...)
##     panel.first
##     plot.xy(xy, type, ...)
##     panel.last
##     if (axes) {
##         localAxis(if (is.null(y)) 
##             xy$x
##         else x, side = 1, gap.axis = xgap.axis, ...)
##         localAxis(if (is.null(y)) 
##             x
##         else y, side = 2, gap.axis = ygap.axis, ...)
##     }
##     if (frame.plot) 
##         localBox(...)
##     if (ann) 
##         localTitle(main = main, sub = sub, xlab = xlab, ylab = ylab, 
##             ...)
##     invisible()
## }
## <bytecode: 0x000000001c885160>
## <environment: namespace:graphics>

Writing Functions

  • Add unnamed arguments to our function for use with sd() and mean()
sd
## function (x, na.rm = FALSE) 
## sqrt(var(if (is.vector(x) || is.factor(x)) x else as.double(x), 
##     na.rm = na.rm))
## <bytecode: 0x0000000018230908>
## <environment: namespace:stats>
mean.default
## function (x, trim = 0, na.rm = FALSE, ...) 
## {
##     if (!is.numeric(x) && !is.complex(x) && !is.logical(x)) {
##         warning("argument is not numeric or logical: returning NA")
##         return(NA_real_)
##     }
##     if (na.rm) 
##         x <- x[!is.na(x)]
##     if (!is.numeric(trim) || length(trim) != 1L) 
##         stop("'trim' must be numeric of length one")
##     n <- length(x)
##     if (trim > 0 && n) {
##         if (is.complex(x)) 
##             stop("trimmed means are not defined for complex data")
##         if (anyNA(x)) 
##             return(NA_real_)
##         if (trim >= 0.5) 
##             return(stats::median(x, na.rm = FALSE))
##         lo <- floor(n * trim) + 1
##         hi <- n + 1 - lo
##         x <- sort.int(x, partial = unique(c(lo, hi)))[lo:hi]
##     }
##     .Internal(mean(x))
## }
## <bytecode: 0x0000000014e129e8>
## <environment: namespace:base>

Writing Functions

  • Add unnamed arguments to our function for use with sd() and mean()
standardize <- function(vector, center = TRUE, scale = TRUE, ...) {
    mean <- mean(vector, ...)
    stdev <- sd(vector, ...)
    if (center) {
        vector <- vector - mean
    }
    if (scale) {
        vector <- vector / stdev
    }
    return(list(result = vector, mean = mean, sd = stdev))
}

Writing Functions

sData <- standardize(airquality$Ozone, na.rm = TRUE)
sData$sd
## [1] 32.98788
sData$result
##   [1] -0.03423409 -0.18580489 -0.91334473 -0.73145977          NA -0.42831817
##   [7] -0.57988897 -0.70114561 -1.03460136          NA -1.06491552 -0.79208809
##  [13] -0.94365889 -0.85271641 -0.73145977 -0.85271641 -0.24643321 -1.09522968
##  [19] -0.36768985 -0.94365889 -1.24680048 -0.94365889 -1.15585800 -0.30706153
##  [25]          NA          NA          NA -0.57988897  0.08702254  2.20901373
##  [31] -0.15549073          NA          NA          NA          NA          NA
##  [37]          NA -0.39800401          NA  0.87519070 -0.09486241          NA
##  [43]          NA -0.57988897          NA          NA -0.64051729 -0.15549073
##  [49] -0.67083145 -0.91334473 -0.88303057          NA          NA          NA
##  [55]          NA          NA          NA          NA          NA          NA
##  [61]          NA  2.81529692  0.20827918 -0.30706153          NA  0.66299158
##  [67] -0.06454825  1.05707566  1.66335885  1.66335885  1.29958893          NA
##  [73] -0.97397305 -0.45863233          NA -1.06491552  0.17796502 -0.21611905
##  [79]  0.57204910  1.11770398  0.63267742 -0.79208809          NA          NA
##  [85]  1.14801813  1.99681461 -0.67083145  0.29922166  1.20864645  0.23859334
##  [91]  0.66299158  0.51142078 -0.09486241 -1.00428721 -0.79208809  1.08738982
##  [97] -0.21611905  0.72361990  2.42121284  1.42084557  2.05744293          NA
## [103]          NA  0.05670838 -0.42831817  0.69330574          NA -0.61020313
## [109]  0.51142078 -0.57988897 -0.33737569  0.05670838 -0.64051729 -1.00428721
## [115]          NA  0.08702254  3.81566419  0.93581902          NA  1.02676150
## [121]  2.29995620  1.26927477  1.29958893  1.63304469  1.08738982  0.93581902
## [127]  1.48147389  0.14765086 -0.30706153 -0.67083145 -0.57988897 -0.64051729
## [133] -0.54957481  0.05670838 -0.64051729 -0.42831817 -1.00428721 -0.88303057
## [139]  0.11733670 -0.73145977 -0.88303057 -0.54957481 -0.79208809 -0.88303057
## [145] -0.57988897 -0.18580489 -1.06491552 -0.85271641 -0.36768985          NA
## [151] -0.85271641 -0.73145977 -0.67083145

Writing Functions

  • Note: You can get at the unnamed arguments with list(...)
f <- function(x, ...){
    unnamed <- names(list(...))
    unnamedVals <- list(...)
    modifyX <- x^2  
    return(list(newX = modifyX, elipNames = unnamed, elipValues = unnamedVals))
}

Writing Functions

f(x = 10, a = 1, b = "hey there", num = 1:3)
## $newX
## [1] 100
## 
## $elipNames
## [1] "a"   "b"   "num"
## 
## $elipValues
## $elipValues$a
## [1] 1
## 
## $elipValues$b
## [1] "hey there"
## 
## $elipValues$num
## [1] 1 2 3

Recap

  • Function writing opens R up!

  • Syntax

nameOfFunction <- function(input1, input2, ...) {
  #code
  #return something with return()
  #or returns last value
}

  • Can set defaults in function definition

  • Can return a named list

  • Can give unnamed arguments for use

Naming conventions and input matching

  • Use of consistent naming schemes is important!

  • Objects

    • must start with a letter
    • can only have letters, numbers, _, and .

Naming conventions and input matching

  • Use of consistent naming schemes is important!

  • Objects

    • must start with a letter
    • can only have letters, numbers, _, and .

  • Functions usually verbs, data objects usually nouns

  • Naming schemes

    • snake_case_used
    • camelCaseUsed
    • UpperCamelCase
    • use.of.periods

Naming conventions and input matching

  • Also need to name inputs! (From R for Data Science)

    • x, y, z: vectors
    • w: a vector of weights
    • df: a data frame
    • i, j: numeric indices (typically rows and columns)
    • n: length, or number of rows
    • p: number of columns

Otherwise, consider matching names of arguments in existing R functions. For example, use na.rm to determine if missing values should be removed.

Naming conventions and input matching

  • Consider the inputs of the cor() function
cor
## function (x, y = NULL, use = "everything", method = c("pearson", 
##     "kendall", "spearman")) 
## {
##     na.method <- pmatch(use, c("all.obs", "complete.obs", "pairwise.complete.obs", 
##         "everything", "na.or.complete"))
##     if (is.na(na.method)) 
##         stop("invalid 'use' argument")
##     method <- match.arg(method)
##     if (is.data.frame(y)) 
##         y <- as.matrix(y)
##     if (is.data.frame(x)) 
##         x <- as.matrix(x)
##     if (!is.matrix(x) && is.null(y)) 
##         stop("supply both 'x' and 'y' or a matrix-like 'x'")
##     if (!(is.numeric(x) || is.logical(x))) 
##         stop("'x' must be numeric")
##     stopifnot(is.atomic(x))
##     if (!is.null(y)) {
##         if (!(is.numeric(y) || is.logical(y))) 
##             stop("'y' must be numeric")
##         stopifnot(is.atomic(y))
##     }
##     Rank <- function(u) {
##         if (length(u) == 0L) 
##             u
##         else if (is.matrix(u)) {
##             if (nrow(u) > 1L) 
##                 apply(u, 2L, rank, na.last = "keep")
##             else row(u)
##         }
##         else rank(u, na.last = "keep")
##     }
##     if (method == "pearson") 
##         .Call(C_cor, x, y, na.method, FALSE)
##     else if (na.method %in% c(2L, 5L)) {
##         if (is.null(y)) {
##             .Call(C_cor, Rank(na.omit(x)), NULL, na.method, method == 
##                 "kendall")
##         }
##         else {
##             nas <- attr(na.omit(cbind(x, y)), "na.action")
##             dropNA <- function(x, nas) {
##                 if (length(nas)) {
##                   if (is.matrix(x)) 
##                     x[-nas, , drop = FALSE]
##                   else x[-nas]
##                 }
##                 else x
##             }
##             .Call(C_cor, Rank(dropNA(x, nas)), Rank(dropNA(y, 
##                 nas)), na.method, method == "kendall")
##         }
##     }
##     else if (na.method != 3L) {
##         x <- Rank(x)
##         if (!is.null(y)) 
##             y <- Rank(y)
##         .Call(C_cor, x, y, na.method, method == "kendall")
##     }
##     else {
##         if (is.null(y)) {
##             ncy <- ncx <- ncol(x)
##             if (ncx == 0) 
##                 stop("'x' is empty")
##             r <- matrix(0, nrow = ncx, ncol = ncy)
##             for (i in seq_len(ncx)) {
##                 for (j in seq_len(i)) {
##                   x2 <- x[, i]
##                   y2 <- x[, j]
##                   ok <- complete.cases(x2, y2)
##                   x2 <- rank(x2[ok])
##                   y2 <- rank(y2[ok])
##                   r[i, j] <- if (any(ok)) 
##                     .Call(C_cor, x2, y2, 1L, method == "kendall")
##                   else NA
##                 }
##             }
##             r <- r + t(r) - diag(diag(r))
##             rownames(r) <- colnames(x)
##             colnames(r) <- colnames(x)
##             r
##         }
##         else {
##             if (length(x) == 0L || length(y) == 0L) 
##                 stop("both 'x' and 'y' must be non-empty")
##             matrix_result <- is.matrix(x) || is.matrix(y)
##             if (!is.matrix(x)) 
##                 x <- matrix(x, ncol = 1L)
##             if (!is.matrix(y)) 
##                 y <- matrix(y, ncol = 1L)
##             ncx <- ncol(x)
##             ncy <- ncol(y)
##             r <- matrix(0, nrow = ncx, ncol = ncy)
##             for (i in seq_len(ncx)) {
##                 for (j in seq_len(ncy)) {
##                   x2 <- x[, i]
##                   y2 <- y[, j]
##                   ok <- complete.cases(x2, y2)
##                   x2 <- rank(x2[ok])
##                   y2 <- rank(y2[ok])
##                   r[i, j] <- if (any(ok)) 
##                     .Call(C_cor, x2, y2, 1L, method == "kendall")
##                   else NA
##                 }
##             }
##             rownames(r) <- colnames(x)
##             colnames(r) <- colnames(y)
##             if (matrix_result) 
##                 r
##             else drop(r)
##         }
##     }
## }
## <bytecode: 0x0000000020688328>
## <environment: namespace:stats>

Naming conventions and input matching

  • Consider the inputs of the cor() function

  • Apply it to iris data…

cor(iris$Sepal.Length, iris$Sepal.Width)
## [1] -0.1175698
  • Notice R doesn’t require names: here it is using positional matching
function (x, y = NULL, use = "everything", method = c("pearson", 
    "kendall", "spearman"))

Naming conventions and input matching

  • Consider the inputs of the cor() function

  • Apply it to iris data…

cor(x = iris$Sepal.Length, method = "spearman", iris$Sepal.Width)
## [1] -0.1667777
  • Positional match for inputs not explicitly called
function (x, y = NULL, use = "everything", method = c("pearson", 
    "kendall", "spearman"))

Naming conventions and input matching

  • Consider the inputs of the cor() function

  • Apply it to iris data…

cor(x = iris$Sepal.Length, met = "spearman", iris$Sepal.Width)
## [1] -0.1667777
  • Partial matching is used if not exactly met!
function (x, y = NULL, use = "everything", method = c("pearson", 
    "kendall", "spearman"))

stop() and switch()

To kick out of a function, you can use stop()

transposeDF <- function(df) {
    if(!is.data.frame(df)){
        stop("I want a data frame only!")
    }
    t(df)
}
transposeDF(iris)
##              [,1]     [,2]     [,3]     [,4]     [,5]     [,6]     [,7]    
## Sepal.Length "5.1"    "4.9"    "4.7"    "4.6"    "5.0"    "5.4"    "4.6"   
## Sepal.Width  "3.5"    "3.0"    "3.2"    "3.1"    "3.6"    "3.9"    "3.4"   
## Petal.Length "1.4"    "1.4"    "1.3"    "1.5"    "1.4"    "1.7"    "1.4"   
## Petal.Width  "0.2"    "0.2"    "0.2"    "0.2"    "0.2"    "0.4"    "0.3"   
## Species      "setosa" "setosa" "setosa" "setosa" "setosa" "setosa" "setosa"
##              [,8]     [,9]     [,10]    [,11]    [,12]    [,13]    [,14]   
## Sepal.Length "5.0"    "4.4"    "4.9"    "5.4"    "4.8"    "4.8"    "4.3"   
## Sepal.Width  "3.4"    "2.9"    "3.1"    "3.7"    "3.4"    "3.0"    "3.0"   
## Petal.Length "1.5"    "1.4"    "1.5"    "1.5"    "1.6"    "1.4"    "1.1"   
## Petal.Width  "0.2"    "0.2"    "0.1"    "0.2"    "0.2"    "0.1"    "0.1"   
## Species      "setosa" "setosa" "setosa" "setosa" "setosa" "setosa" "setosa"
##              [,15]    [,16]    [,17]    [,18]    [,19]    [,20]    [,21]   
## Sepal.Length "5.8"    "5.7"    "5.4"    "5.1"    "5.7"    "5.1"    "5.4"   
## Sepal.Width  "4.0"    "4.4"    "3.9"    "3.5"    "3.8"    "3.8"    "3.4"   
## Petal.Length "1.2"    "1.5"    "1.3"    "1.4"    "1.7"    "1.5"    "1.7"   
## Petal.Width  "0.2"    "0.4"    "0.4"    "0.3"    "0.3"    "0.3"    "0.2"   
## Species      "setosa" "setosa" "setosa" "setosa" "setosa" "setosa" "setosa"
##              [,22]    [,23]    [,24]    [,25]    [,26]    [,27]    [,28]   
## Sepal.Length "5.1"    "4.6"    "5.1"    "4.8"    "5.0"    "5.0"    "5.2"   
## Sepal.Width  "3.7"    "3.6"    "3.3"    "3.4"    "3.0"    "3.4"    "3.5"   
## Petal.Length "1.5"    "1.0"    "1.7"    "1.9"    "1.6"    "1.6"    "1.5"   
## Petal.Width  "0.4"    "0.2"    "0.5"    "0.2"    "0.2"    "0.4"    "0.2"   
## Species      "setosa" "setosa" "setosa" "setosa" "setosa" "setosa" "setosa"
##              [,29]    [,30]    [,31]    [,32]    [,33]    [,34]    [,35]   
## Sepal.Length "5.2"    "4.7"    "4.8"    "5.4"    "5.2"    "5.5"    "4.9"   
## Sepal.Width  "3.4"    "3.2"    "3.1"    "3.4"    "4.1"    "4.2"    "3.1"   
## Petal.Length "1.4"    "1.6"    "1.6"    "1.5"    "1.5"    "1.4"    "1.5"   
## Petal.Width  "0.2"    "0.2"    "0.2"    "0.4"    "0.1"    "0.2"    "0.2"   
## Species      "setosa" "setosa" "setosa" "setosa" "setosa" "setosa" "setosa"
##              [,36]    [,37]    [,38]    [,39]    [,40]    [,41]    [,42]   
## Sepal.Length "5.0"    "5.5"    "4.9"    "4.4"    "5.1"    "5.0"    "4.5"   
## Sepal.Width  "3.2"    "3.5"    "3.6"    "3.0"    "3.4"    "3.5"    "2.3"   
## Petal.Length "1.2"    "1.3"    "1.4"    "1.3"    "1.5"    "1.3"    "1.3"   
## Petal.Width  "0.2"    "0.2"    "0.1"    "0.2"    "0.2"    "0.3"    "0.3"   
## Species      "setosa" "setosa" "setosa" "setosa" "setosa" "setosa" "setosa"
##              [,43]    [,44]    [,45]    [,46]    [,47]    [,48]    [,49]   
## Sepal.Length "4.4"    "5.0"    "5.1"    "4.8"    "5.1"    "4.6"    "5.3"   
## Sepal.Width  "3.2"    "3.5"    "3.8"    "3.0"    "3.8"    "3.2"    "3.7"   
## Petal.Length "1.3"    "1.6"    "1.9"    "1.4"    "1.6"    "1.4"    "1.5"   
## Petal.Width  "0.2"    "0.6"    "0.4"    "0.3"    "0.2"    "0.2"    "0.2"   
## Species      "setosa" "setosa" "setosa" "setosa" "setosa" "setosa" "setosa"
##              [,50]    [,51]        [,52]        [,53]        [,54]       
## Sepal.Length "5.0"    "7.0"        "6.4"        "6.9"        "5.5"       
## Sepal.Width  "3.3"    "3.2"        "3.2"        "3.1"        "2.3"       
## Petal.Length "1.4"    "4.7"        "4.5"        "4.9"        "4.0"       
## Petal.Width  "0.2"    "1.4"        "1.5"        "1.5"        "1.3"       
## Species      "setosa" "versicolor" "versicolor" "versicolor" "versicolor"
##              [,55]        [,56]        [,57]        [,58]        [,59]       
## Sepal.Length "6.5"        "5.7"        "6.3"        "4.9"        "6.6"       
## Sepal.Width  "2.8"        "2.8"        "3.3"        "2.4"        "2.9"       
## Petal.Length "4.6"        "4.5"        "4.7"        "3.3"        "4.6"       
## Petal.Width  "1.5"        "1.3"        "1.6"        "1.0"        "1.3"       
## Species      "versicolor" "versicolor" "versicolor" "versicolor" "versicolor"
##              [,60]        [,61]        [,62]        [,63]        [,64]       
## Sepal.Length "5.2"        "5.0"        "5.9"        "6.0"        "6.1"       
## Sepal.Width  "2.7"        "2.0"        "3.0"        "2.2"        "2.9"       
## Petal.Length "3.9"        "3.5"        "4.2"        "4.0"        "4.7"       
## Petal.Width  "1.4"        "1.0"        "1.5"        "1.0"        "1.4"       
## Species      "versicolor" "versicolor" "versicolor" "versicolor" "versicolor"
##              [,65]        [,66]        [,67]        [,68]        [,69]       
## Sepal.Length "5.6"        "6.7"        "5.6"        "5.8"        "6.2"       
## Sepal.Width  "2.9"        "3.1"        "3.0"        "2.7"        "2.2"       
## Petal.Length "3.6"        "4.4"        "4.5"        "4.1"        "4.5"       
## Petal.Width  "1.3"        "1.4"        "1.5"        "1.0"        "1.5"       
## Species      "versicolor" "versicolor" "versicolor" "versicolor" "versicolor"
##              [,70]        [,71]        [,72]        [,73]        [,74]       
## Sepal.Length "5.6"        "5.9"        "6.1"        "6.3"        "6.1"       
## Sepal.Width  "2.5"        "3.2"        "2.8"        "2.5"        "2.8"       
## Petal.Length "3.9"        "4.8"        "4.0"        "4.9"        "4.7"       
## Petal.Width  "1.1"        "1.8"        "1.3"        "1.5"        "1.2"       
## Species      "versicolor" "versicolor" "versicolor" "versicolor" "versicolor"
##              [,75]        [,76]        [,77]        [,78]        [,79]       
## Sepal.Length "6.4"        "6.6"        "6.8"        "6.7"        "6.0"       
## Sepal.Width  "2.9"        "3.0"        "2.8"        "3.0"        "2.9"       
## Petal.Length "4.3"        "4.4"        "4.8"        "5.0"        "4.5"       
## Petal.Width  "1.3"        "1.4"        "1.4"        "1.7"        "1.5"       
## Species      "versicolor" "versicolor" "versicolor" "versicolor" "versicolor"
##              [,80]        [,81]        [,82]        [,83]        [,84]       
## Sepal.Length "5.7"        "5.5"        "5.5"        "5.8"        "6.0"       
## Sepal.Width  "2.6"        "2.4"        "2.4"        "2.7"        "2.7"       
## Petal.Length "3.5"        "3.8"        "3.7"        "3.9"        "5.1"       
## Petal.Width  "1.0"        "1.1"        "1.0"        "1.2"        "1.6"       
## Species      "versicolor" "versicolor" "versicolor" "versicolor" "versicolor"
##              [,85]        [,86]        [,87]        [,88]        [,89]       
## Sepal.Length "5.4"        "6.0"        "6.7"        "6.3"        "5.6"       
## Sepal.Width  "3.0"        "3.4"        "3.1"        "2.3"        "3.0"       
## Petal.Length "4.5"        "4.5"        "4.7"        "4.4"        "4.1"       
## Petal.Width  "1.5"        "1.6"        "1.5"        "1.3"        "1.3"       
## Species      "versicolor" "versicolor" "versicolor" "versicolor" "versicolor"
##              [,90]        [,91]        [,92]        [,93]        [,94]       
## Sepal.Length "5.5"        "5.5"        "6.1"        "5.8"        "5.0"       
## Sepal.Width  "2.5"        "2.6"        "3.0"        "2.6"        "2.3"       
## Petal.Length "4.0"        "4.4"        "4.6"        "4.0"        "3.3"       
## Petal.Width  "1.3"        "1.2"        "1.4"        "1.2"        "1.0"       
## Species      "versicolor" "versicolor" "versicolor" "versicolor" "versicolor"
##              [,95]        [,96]        [,97]        [,98]        [,99]       
## Sepal.Length "5.6"        "5.7"        "5.7"        "6.2"        "5.1"       
## Sepal.Width  "2.7"        "3.0"        "2.9"        "2.9"        "2.5"       
## Petal.Length "4.2"        "4.2"        "4.2"        "4.3"        "3.0"       
## Petal.Width  "1.3"        "1.2"        "1.3"        "1.3"        "1.1"       
## Species      "versicolor" "versicolor" "versicolor" "versicolor" "versicolor"
##              [,100]       [,101]      [,102]      [,103]      [,104]     
## Sepal.Length "5.7"        "6.3"       "5.8"       "7.1"       "6.3"      
## Sepal.Width  "2.8"        "3.3"       "2.7"       "3.0"       "2.9"      
## Petal.Length "4.1"        "6.0"       "5.1"       "5.9"       "5.6"      
## Petal.Width  "1.3"        "2.5"       "1.9"       "2.1"       "1.8"      
## Species      "versicolor" "virginica" "virginica" "virginica" "virginica"
##              [,105]      [,106]      [,107]      [,108]      [,109]     
## Sepal.Length "6.5"       "7.6"       "4.9"       "7.3"       "6.7"      
## Sepal.Width  "3.0"       "3.0"       "2.5"       "2.9"       "2.5"      
## Petal.Length "5.8"       "6.6"       "4.5"       "6.3"       "5.8"      
## Petal.Width  "2.2"       "2.1"       "1.7"       "1.8"       "1.8"      
## Species      "virginica" "virginica" "virginica" "virginica" "virginica"
##              [,110]      [,111]      [,112]      [,113]      [,114]     
## Sepal.Length "7.2"       "6.5"       "6.4"       "6.8"       "5.7"      
## Sepal.Width  "3.6"       "3.2"       "2.7"       "3.0"       "2.5"      
## Petal.Length "6.1"       "5.1"       "5.3"       "5.5"       "5.0"      
## Petal.Width  "2.5"       "2.0"       "1.9"       "2.1"       "2.0"      
## Species      "virginica" "virginica" "virginica" "virginica" "virginica"
##              [,115]      [,116]      [,117]      [,118]      [,119]     
## Sepal.Length "5.8"       "6.4"       "6.5"       "7.7"       "7.7"      
## Sepal.Width  "2.8"       "3.2"       "3.0"       "3.8"       "2.6"      
## Petal.Length "5.1"       "5.3"       "5.5"       "6.7"       "6.9"      
## Petal.Width  "2.4"       "2.3"       "1.8"       "2.2"       "2.3"      
## Species      "virginica" "virginica" "virginica" "virginica" "virginica"
##              [,120]      [,121]      [,122]      [,123]      [,124]     
## Sepal.Length "6.0"       "6.9"       "5.6"       "7.7"       "6.3"      
## Sepal.Width  "2.2"       "3.2"       "2.8"       "2.8"       "2.7"      
## Petal.Length "5.0"       "5.7"       "4.9"       "6.7"       "4.9"      
## Petal.Width  "1.5"       "2.3"       "2.0"       "2.0"       "1.8"      
## Species      "virginica" "virginica" "virginica" "virginica" "virginica"
##              [,125]      [,126]      [,127]      [,128]      [,129]     
## Sepal.Length "6.7"       "7.2"       "6.2"       "6.1"       "6.4"      
## Sepal.Width  "3.3"       "3.2"       "2.8"       "3.0"       "2.8"      
## Petal.Length "5.7"       "6.0"       "4.8"       "4.9"       "5.6"      
## Petal.Width  "2.1"       "1.8"       "1.8"       "1.8"       "2.1"      
## Species      "virginica" "virginica" "virginica" "virginica" "virginica"
##              [,130]      [,131]      [,132]      [,133]      [,134]     
## Sepal.Length "7.2"       "7.4"       "7.9"       "6.4"       "6.3"      
## Sepal.Width  "3.0"       "2.8"       "3.8"       "2.8"       "2.8"      
## Petal.Length "5.8"       "6.1"       "6.4"       "5.6"       "5.1"      
## Petal.Width  "1.6"       "1.9"       "2.0"       "2.2"       "1.5"      
## Species      "virginica" "virginica" "virginica" "virginica" "virginica"
##              [,135]      [,136]      [,137]      [,138]      [,139]     
## Sepal.Length "6.1"       "7.7"       "6.3"       "6.4"       "6.0"      
## Sepal.Width  "2.6"       "3.0"       "3.4"       "3.1"       "3.0"      
## Petal.Length "5.6"       "6.1"       "5.6"       "5.5"       "4.8"      
## Petal.Width  "1.4"       "2.3"       "2.4"       "1.8"       "1.8"      
## Species      "virginica" "virginica" "virginica" "virginica" "virginica"
##              [,140]      [,141]      [,142]      [,143]      [,144]     
## Sepal.Length "6.9"       "6.7"       "6.9"       "5.8"       "6.8"      
## Sepal.Width  "3.1"       "3.1"       "3.1"       "2.7"       "3.2"      
## Petal.Length "5.4"       "5.6"       "5.1"       "5.1"       "5.9"      
## Petal.Width  "2.1"       "2.4"       "2.3"       "1.9"       "2.3"      
## Species      "virginica" "virginica" "virginica" "virginica" "virginica"
##              [,145]      [,146]      [,147]      [,148]      [,149]     
## Sepal.Length "6.7"       "6.7"       "6.3"       "6.5"       "6.2"      
## Sepal.Width  "3.3"       "3.0"       "2.5"       "3.0"       "3.4"      
## Petal.Length "5.7"       "5.2"       "5.0"       "5.2"       "5.4"      
## Petal.Width  "2.5"       "2.3"       "1.9"       "2.0"       "2.3"      
## Species      "virginica" "virginica" "virginica" "virginica" "virginica"
##              [,150]     
## Sepal.Length "5.9"      
## Sepal.Width  "3.0"      
## Petal.Length "5.1"      
## Petal.Width  "1.8"      
## Species      "virginica"

stop() and switch()

To kick out of a function, you can use stop()

transposeDF <- function(df) {
    if(!is.data.frame(df)){
        stop("I want a data frame only!")
    }
    t(df)
}
transposeDF(as.matrix(iris))
## Error in transposeDF(as.matrix(iris)): I want a data frame only!

stop() and switch()

Often you want to check on inputs, can use if() or switch()

center <- function(vec, type, ...) {
  if(!is.vector(vec)){
    stop("Not a vector my friend.")
  }
    switch(type, 
                 mean = vec - mean(vec),
                 median = vec - median(vec),
                 trimmed = vec - mean(vec, ...),
                 stop("Mistake!")
    )
}
center(c(1,1,1,6,10), "mean")
## [1] -2.8 -2.8 -2.8  2.2  6.2

stop() and switch()

Often you want to check on inputs, can use if() or switch()

center <- function(vec, type, ...) {
  if(!is.vector(vec)){
    stop("Not a vector my friend.")
  }
    switch(type, 
                 mean = vec - mean(vec),
                 median = vec - median(vec),
                 trimmed = vec - mean(vec, ...),
                 stop("Mistake!")
    )
}
center(c(1,1,1,6,10), "median")
## [1] 0 0 0 5 9

stop() and switch()

Often you want to check on inputs, can use if() or switch()

center <- function(vec, type, ...) {
  if(!is.vector(vec)){
    stop("Not a vector my friend.")
  }
    switch(type, 
                 mean = vec - mean(vec),
                 median = vec - median(vec),
                 trimmed = vec - mean(vec, ...),
                 stop("Mistake!")
    )
}
center(c(1,1,1,6,10), "trimmed", trim = 0.2)
## [1] -1.666667 -1.666667 -1.666667  3.333333  7.333333

stop() and switch()

Often you want to check on inputs, can use if() or switch()

center <- function(vec, type, ...) {
    if(!is.vector(vec)){
        stop("Not a vector my friend.")
    }
    if(type == "mean"){
        vec - mean(vec)
    } else if (type =="median"){
        vec - median(vec)
    } else if (type =="trimmed") {
        vec - mean(vec, ...)
    } else {
        stop("Mistake!")
    }
}
center(c(1,1,1,6,10), "trimmed", trim = 0.2)
## [1] -1.666667 -1.666667 -1.666667  3.333333  7.333333

Quick Examples

Writing Pipeable functions

  • Two types of pipeable functions:

    1. transformations
    2. side-effects

Pipeable functions

  • Two types of pipeable functions:

    1. transformations
    2. side-effects

  • transformations naturally return the modified argument (df)

  • side-effects don’t - usually a plot, saving a file, etc.
  • can silently return df with invisible()

Pipeable functions

  • Two types of pipeable functions:

    1. transformations
    2. side-effects
printNumObs <- function(df) {
    cat("The number of observations in the data set is ", nrow(df), "\n", sep = "")
}
iris %>% printNumObs %>% summarize(mean = mean(Sepal.Length))
## The number of observations in the data set is 150
## Error in UseMethod("summarise"): no applicable method for 'summarise' applied to an object of class "NULL"

Pipeable functions

  • Two types of pipeable functions:

    1. transformations
    2. side-effects
printNumObs <- function(df) {
    cat("The number of observations in the data set is ", nrow(df), "\n", sep = "")
    invisible(df)
}
iris %>% printNumObs %>% summarize(mean = mean(Sepal.Length))
## The number of observations in the data set is 150
##       mean
## 1 5.843333

Pipeable functions

printNumObs <- function(df) {
    cat("The number of observations in the data set is ", nrow(df), "\n", sep = "")
    invisible(df)
}
temp <- printNumObs(iris)
## The number of observations in the data set is 150
str(temp)
## 'data.frame':    150 obs. of  5 variables:
##  $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
##  $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
##  $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
##  $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
##  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...

Infix functions

  • Speaking of pipes…

  • Infix function - a function that goes between arguments (as opposed to prefix)

mean(3:5) #prefix
## [1] 4
3 + 5 #+ is infix
## [1] 8
`+`(3, 5) #used as a prefix function
## [1] 8

Infix functions

  • Infix function - a function that goes between arguments (as opposed to prefix)

  • Common built-in infix functions include: ::, $, ^, *, /, +, -, >, >=, <, <=, ==, !=, &, |, <-

  • Others use %symbol% syntax: %*% (matrix multiplication), %in% (check if LHS value(s) is(are) in RHS value(s)

  • Can call like prefix functions

cars <- as.matrix(cars)
t(cars) %*% cars
##       speed   dist
## speed 13228  38482
## dist  38482 124903
`%*%`(t(cars), cars)
##       speed   dist
## speed 13228  38482
## dist  38482 124903

Infix functions

  • Infix function - a function that goes between arguments (as opposed to prefix)

  • Can write your own!

`%+%` <- function(a, b) paste0(a, b)
"new" %+% " string"
## [1] "new string"
  • Can overwrite + and other operators: just don’t do that…

Infix functions

  • Infix function - a function that goes between arguments (as opposed to prefix)

  • Can use precendence rules to save typing

x <- y <- 2
`<-`(x, `<-`(y, 2)) #interpretation of above code!

x <- y = 2# error! <- has higher precedence
`=`(`<-`(x, y), 2) #interpretation of above code!

x = y <- 2 # this will work!
`=`(x, `<-`(y, 2)) #interpretation of above code!

Infix functions

  • Infix function - a function that goes between arguments (as opposed to prefix)

  • Can use precendence rules to save typing

`%-%` <- function(a, b) {
    paste0("(", a, " %-% ", b, ")")
}
"a" %-% "b" %-% "c" #user defined infix are evaluated left to right!
## [1] "((a %-% b) %-% c)"
`%-%`(`%-%`("a", "b"), "c")  #interpretation of above code!
## [1] "((a %-% b) %-% c)"

Environments and Lexical Scoping

  • R objects live in an environment

  • You can think of it as a “bag of names” that point to things in memory

  • Like a list but with no ordering (and other things)

Environments and Lexical Scoping

  • Environments have ‘parents’ and ‘children’

    • Global environment is where our created function objects live

    • Search path has all packages loaded in (most recent package is the parent of the global environment)

    • base environment is the child of the ultimate ancestor, the empty environment

Environments and Lexical Scoping

  • Environments have ‘parents’ and ‘children’

    • Global environment is where our created function objects live

    • Search path has all packages loaded in (most recent package is the parent of the global environment)

    • base environment is the child of the ultimate ancestor, the empty environment

##  [1] ".GlobalEnv"        "package:knitr"     "package:forcats"  
##  [4] "package:stringr"   "package:dplyr"     "package:purrr"    
##  [7] "package:readr"     "package:tidyr"     "package:tibble"   
## [10] "package:ggplot2"   "package:tidyverse" "package:stats"    
## [13] "package:graphics"  "package:grDevices" "package:utils"    
## [16] "package:datasets"  "package:methods"   "Autoloads"        
## [19] "package:base"

Environments and Lexical Scoping

  • Don’t need to fully understand them… a few important things to know
library(pryr) #install if needed
x <- "hey"
where("x")
## <environment: R_GlobalEnv>
where("mean")
## <environment: base>

Environments and Lexical Scoping

  • When you call a function, it creates temporary function environments

  • This is why variables in functions don’t overwrite things (mean still exists as is!)

f <- function(x){
    mean <- paste0(x, " is a value")
    mean
}
f(1:3)
## [1] "1 is a value" "2 is a value" "3 is a value"
mean
## function (x, ...) 
## UseMethod("mean")
## <bytecode: 0x0000000017e89428>
## <environment: namespace:base>

Environments and Lexical Scoping

  • When you call a function, it creates temporary function environments
g <- function(x) {
  if (!exists("a", inherits = FALSE)) {
    message("Defining a")
    a <- 1
  } else {
    a <- a + 1
  }
  a
}
#Running the function doesn't create 
#the a object in our global environment!
g(10)
## Defining a
## [1] 1
g(10)
## Defining a
## [1] 1

Environments and Lexical Scoping

  • When you call a function, it creates temporary function environments

  • This is why variables can have the same name in a function and in your global environment

y <- 10
f <- function(x){
    y <- 1
    x + y
}
f(15)
## [1] 16

Environments and Lexical Scoping

  • If R doesn’t find an object in the current environment, it will search up the path
y <- 1
f <- function(x){
    x + y
}
f(10)
## [1] 11
  • Much more to it, but this should give you a strong foundation

Quick Examples