Chapter 15 For loops

Here we are going to learn how to write a for loop to download some data and name files. We will do two sites for simplicity, but this can be fed as many sites as you wish!

15.1 Libraries

library(tidyverse)
library(dataRetrieval)

15.2 Defining parameters

You could type out the sites and names or you could pull it from some whatNWISsites call.

sites <- c("06037500", "12363000")
names <- c("salmon", "flathead")
params <- c("00060", "00010") # This is temperature and Q. You can obviously change and then also change the readNWISdata to something else and the parameters, etc. 
start <- as_date("1900-10-01") # Just a nice round number for start time. 
end <- as_date("2023-09-30") #End of last water year. 
service <- "dv" # Daily values

# Removed those sites for testing
# "12363000", "13296000", "12344000", "12447200", "13331500", "06191500"

15.3 Writing the for loop

Instead of writing a function, we use for(i in sites). So this will run through the list of sites and download the data and do whatever else you tell it. Then we create a filename that is data_, i. So it will write out data_06037500.csv for the first, data_12363000.csv for the second, so on. Then I just read the .csv in to check and make sure it worked.

for (i in sites) {
  tmp <- readNWISdata(sites = i, parameterCd = params, service = service, startDate = start, endDate = end) %>% 
    renameNWISColumns()
  filename <- paste("data_", i, sep="")
  write_csv(tmp, file = paste(filename, ".csv", sep=""))
}

test_df <- read_csv("data_06037500.csv")

15.4 Adding second for

Here, I’ve added a second for. For i in sites and for j in names. So when we get to the naming we look to the j for the name to put that in the title of the .csv

for (i in sites) {
  for (j in names) {
  tmp <- readNWISdata(sites = i, parameterCd = params, service = service, startDate = start, endDate = end) %>% 
    renameNWISColumns()
  filename <- paste("data_", j, sep="")
  write_csv(tmp, file = paste(filename, ".csv", sep=""))
  }
}

test_df <- read_csv("data_salmon.csv")

15.5 Removing the tmp file

This does the same thing, just removes the tmp file at the end to clean up the global environment.

for (i in sites) {
  for (j in names) {
  tmp <- readNWISdata(sites = i, parameterCd = params, service = service, startDate = start, endDate = end) %>% 
    renameNWISColumns()
  assign(paste("data_", j, sep=""), tmp)
  rm(tmp) 
  }
}