Introduction

In this example I’ll show some basic examples of for() loops in R using toy examples. Then build some for() loops to address some practical problems, including running a series of regession models. I’ll also show how to debug them by putting them into a function().

Toy examples

I’ll start off with some toy examples to illustrate basic functionality.

Toy example 1

What: For each number 1 through 10, square it and print it out.
for() starts te loop
“i” means in index value
“for i in 1:10” means “for each value of i ranging from 1 to 10”
print() returns output to the R console.


for(i in 1:10){
  print(i^2)
}

## [1] 1
## [1] 4
## [1] 9
## [1] 16
## [1] 25
## [1] 36
## [1] 49
## [1] 64
## [1] 81
## [1] 100

Toy example 2

Square each value and save it into a vector

First, a vector to hold the data

#replicate the value NA 10 times
storage.vector <- rep(NA,10)

For each value 1 to 10 square it and save it into storage.vector


for(i in 1:10){
  storage.vector[i] <- i^2
}

Look at the output

storage.vector

##  [1]   1   4   9  16  25  36  49  64  81 100

Toy example 3

Draw values from a dataframe, square them, then store them to a dataframe.

First, Make a dataframe to hold the output of the loop

Setup

A list of values (technicall a vector)

values <- c(1,3,6,12,24,48)

A dataframe holding thse values, and a blank row to hold the output.

output.df <- data.frame(value  = values,
                        value.squared = NA)

output.df

##   value value.squared
## 1     1            NA
## 2     3            NA
## 3     6            NA
## 4    12            NA
## 5    24            NA
## 6    48            NA

Equivalently we could do this

output.df <- data.frame(value  = c(1,3,6,12,24,48),
                        value.squared = NA)

The number of values

n.values <- length(values)

Or equivalently, using the dataframe

n.values <- dim(output.df)[1]

The for() loop

Loop over the i values and square

for (i in 1:n.values){
  
  #get value in row i of the "i" column
  i.current <- output.df[i,"value"]
  
  #square it
  i.squared <- i.current^2
  
  #save it to dataframe
  output.df[i,"value.squared"] <- i.squared
}

output.df

##   value value.squared
## 1     1             1
## 2     3             9
## 3     6            36
## 4    12           144
## 5    24           576
## 6    48          2304

Debugging a for loop

A useful way to debug for() loops is to put them into function
Code must be modified a bit
Must include return() to actually output from the function the output of the loop
If you want to save the output need to assign it an object

The for loop

loop.in.function <- function(){
  for (i in 1:n.values){
  
  #get value in row i of the "i" column
  i.current <- output.df[i,"value"]
  
  #square it
  i.squared <- i.current^2
  
  #save it to dataframe
  output.df[i,"value.squared"] <- i.squared
}

  #a helpful reminder
  cat("NOTE: If you want to save the output, must assign it to an object")
  
  
  #MUST INCLUDE return() to send output out of function land
  return(output.df)
  

}

Run the loop

loop.in.function()

## NOTE: If you want to save the output, must assign it to an object

##   value value.squared
## 1     1             1
## 2     3             9
## 3     6            36
## 4    12           144
## 5    24           576
## 6    48          2304

If you need to debug

debugonce(loop.in.function)

Toy example 4

For each species in a dataset, how many rows does that species occur in. There are easier ways to anwer this question; this is just for illustration.

Set up data

Load data for Lloyd et al 2016 PeerJ paper.

dat <- read.csv(file = "PALO_data.csv")

Look at data

head(dat)

##   Location Species Year Session spp.ann.tot net.hours tot.years.obs
## 1     PALO    BAWW 1997      NA           0        NA             4
## 2     PALO    BAWW 2007      NA           0        NA             4
## 3     PALO    BAWW 2002       1           1     941.0             4
## 4     PALO    BAWW 2010       1           1    1095.0             4
## 5     PALO    BAWW 2008       1           1     591.5             4
## 6     PALO    BAWW 2003      NA           0        NA             4
##   caps.per.1K.nethours net.hours.log
## 1                   NA            NA
## 2                   NA            NA
## 3             1.062699      6.846943
## 4             0.913242      6.998510
## 5             1.690617      6.382662
## 6                   NA            NA

Prep: vectors holding preliminary info

unique() extracts each unqiue species name

species.vector <- unique(dat$Species)

The vector has 23 elements, one for each species. Use length() to determine the number of elements and save it.

n.spp <- length(species.vector)

A vector index values, 1 through the number of species


index.values <- 1:n.spp

Dataframe to hold output

output <- data.frame(species.vector,
                     N.rows = NA)

The Loop

We can loop over each species and determine how many rows of that species there are


for(i in index.values){
  
  #extract current species
  current.spp <- species.vector[i]
  
  #determine which rows of the datset have $spp that matches
  #the current species
  index.current.spp <- which(dat$Species == current.spp)
  
  #determine the length of index.current.spp
  #to count up the number of rows
  n.current.spp <- length(index.current.spp)
  
  #save the output to the row of the dataframe
  #corresponding to the current
  #species
  output$N.rows[i] <- n.current.spp
}

Toy example 4 revised

I could write this with less preliminary code

#vector of each species
species.vector <- unique(dat$Species)

#dataframe to hold output
output <- data.frame(species.vector,
                     N.rows = NA)

for(i in 1:length(species.vector)){
  

  index.current.spp <- which(dat$Species ==   species.vector[i])
  
  output$N.rows[i] <- length(index.current.spp)
}
output

##    species.vector N.rows
## 1            BAWW     11
## 2            BCPT     11
## 3            BITH     11
## 4            BTBW     11
## 5            GABU     11
## 6            GAEL     11
## 7            GTGT     11
## 8            HHTA     11
## 9            HIEM     11
## 10           HIPE     11
## 11           HISP     11
## 12           HITR     11
## 13           HIWO     11
## 14           LATH     11
## 15           NBTO     11
## 16           OVEN     11
## 17           RLTH     11
## 18           RTSO     11
## 19           SSHA     11
## 20           WCHT     11

Debugging for() loops

A useful way to debug for() loops is to put them into function
Must include return() to actually output from the function the output of the loop

Putting a function into a for() loop

Code must be modified a bit
Have to explicity “return” the output of the loop
If you want to save the output need to assign it an object

function.for <- function() {
  for(i in 1:length(species.vector)){
  

  index.current.spp <- which(dat$Species ==   species.vector[i])
  
  output$N.rows[i] <- length(index.current.spp)
  
  }
  
  # must return output of the function!
  return(output)
}

Run the for loop by calling the function

function.for()

##    species.vector N.rows
## 1            BAWW     11
## 2            BCPT     11
## 3            BITH     11
## 4            BTBW     11
## 5            GABU     11
## 6            GAEL     11
## 7            GTGT     11
## 8            HHTA     11
## 9            HIEM     11
## 10           HIPE     11
## 11           HISP     11
## 12           HITR     11
## 13           HIWO     11
## 14           LATH     11
## 15           NBTO     11
## 16           OVEN     11
## 17           RLTH     11
## 18           RTSO     11
## 19           SSHA     11
## 20           WCHT     11

To save the output of the function must assign it to an object

output <- function.for()
output

##    species.vector N.rows
## 1            BAWW     11
## 2            BCPT     11
## 3            BITH     11
## 4            BTBW     11
## 5            GABU     11
## 6            GAEL     11
## 7            GTGT     11
## 8            HHTA     11
## 9            HIEM     11
## 10           HIPE     11
## 11           HISP     11
## 12           HITR     11
## 13           HIWO     11
## 14           LATH     11
## 15           NBTO     11
## 16           OVEN     11
## 17           RLTH     11
## 18           RTSO     11
## 19           SSHA     11
## 20           WCHT     11

Debugging a loop in a function

Call debugonce() on the function

debugonce(function.for)

A real for() loop

The Lloyd data contains time series of counts on 23 species of birds. The following loop runs a regression on each species and saves the output.

Dataframe to hold coefficients

species.vector <- unique(dat$Species)

output.df <- data.frame(Species = species.vector,
                        intercept = NA,
                         year = NA)



regression.loop <- function(){
  for(i in 1:length(species.vector)){
  
  spp.index <- which(dat$Species ==  
                        species.vector[i])
  
  data.subset <- dat[spp.index,]
  
  
  glm.out <- glm(spp.ann.tot ~ Year, 
      data.subset, 
      family = "poisson",
      offset = net.hours.log)
  
  output.df[i,c("intercept",
                "year")] <- coef(glm.out)
  
  
  }
  
  return(output.df)
}

Run it


output <- regression.loop()

head(output)

##   Species intercept        year
## 1    BAWW -53.89253  0.02355041
## 2    BCPT -72.89729  0.03340652
## 3    BITH  10.34299 -0.00777472
## 4    BTBW -93.09204  0.04367571
## 5    GABU  24.57528 -0.01528563
## 6    GAEL 137.06044 -0.07159340

for() loops in R

brouwern@gmail.com

February 21, 2017