Basic for loops
- Let us do the same thing for a number of different values
for (item in list_of_items) {
commands
}
- When you run a for loop the first time through…
Example
pets <- c("spot", "gigantor", "fluffy")
for (pet in pets) {
paste(pet, "is the name of the class pet")
}
What this does:
pets <- c("spot", "gigantor", "fluffy")
pet <- pets[1]
paste(pet, "is the name of the class pet")
pet <- pets[2]
paste(pet, "is the name of the class pet")
pet <- pets[3]
paste(pet, "is the name of the class pet")
Storing results
- Create something to store them
- Add your new values each trip through the loop
library(stringr)
pets <- c("spot", "gigantor", "fluffy")
output <- data.frame()
for (pet in pets) {
pet_upper <- str_to_upper(pet)
output <- rbind(output, data.frame(name = pet_upper,
namelength = str_length(pet_upper)))
}
Looping over columns in data frames
biomass_data <- data.frame(exper1 = c(24, 32, 62),
exper2 = c(10, 9 , 5),
exper3 = c(1, 5, 3))
for (exp_biomass in biomass_data) {
npp <- sum(19.3 * exp_biomass ** 2)
print(npp)
}
Complete through exercise 4
Apply
- Short cuts for simple loops
get_mass_from_length_theropoda <- function(length) {
mass <- 0.73 * length ** 3.63
return(mass)
}
lengths = c(5, 10, 15)
lapply(lengths, FUN = get_mass_from_length_theropoda)
sapply(lengths, FUN = get_mass_from_length_theropoda)
- There are also versions that allow you to pass multiple parameters or operate across either rows or columns
- Arguments for apply:
- speed (avoid premature optimization)
- readability
- Also keep in mind that many functions in R will be vectorized
get_mass_from_length(lengths, as, bs)
MAKE SURE BASICS MAKE SENSE BEFORE COVERING THIS
Dplyr
- Many kinds of looping over data can also be handled using functions in dplyr
estimate_mass <- function(hindfoot_length, weight){
mass
}
surveys <- read.csv("surveys.csv")
Indexing
pets <- c("spot", "gigantor", "fluffy")
owners <- c("betty", "bob", "joe")
for (i in seq_along(pets)){
print(paste(pets[i], "is ", owners[i], "'s pet"))
}
Preallocating memory
library(stringr)
pets <- c("spot", "gigantor", "fluffy")
output <- data.frame(name = character(3), namelength = numeric(3),
stringsAsFactors = FALSE)
for (i in seq_along(pets)) {
pet_upper <- str_to_upper(pets[i])
output[i,] <- c(pet_upper, str_length(pet_upper))
}