R for loop - appending results outside the loop - r

Question

I'm taking an introductory R-programming course on Cousera. The first assignment has us evaluating a list of hundreds of csv files in a specified directory ("./specdata/). Each csv file, in turn, contains hundreds of records of sample pollutant data in the atmosphere - a date, a sulfite sample, a nitrate sample, and an ID of that identifies the sampling location.
The assignment asks us to create a function that takes the pollutant an id or range of ids for sampling location and returns a sample mean, given the supplied arguments.
My code (below) uses a for loop to use the id argument to only read the files of interest (seems more efficient than reading in all 322 files before doing any processing). That works great.
Within the loop, I assign the contents of the csv file to a variable. I then make that variable a data frame and use rbind to append to it the file read in during each loop. I use na.omit to remove the missing files from the variable. Then I use rbind to append the result of each iteration of the loop to variable. When I print the data frame variable within the loop, I can see the entire full list, subgrouped by id. But when I print the variable outside the loop, I only see the last element in the id vector.
I would like to create a consolidated list of all records matching the id argument within the loop, then pass the consolidate list outside the loop for further processing. I can't get this to work. My code is shown below.
Is this the wrong approach? Seems like it could work. Any help would be most appreciated. I searched StackOverflow and couldn't find anything that quite addresses what I'm trying to do.
pmean <- function(directory = "./specdata/", pollutant, id = 1:322) {
x <- list.files(path=directory, pattern="*.csv")
x <- paste(directory, x, sep="")
id1 <- id[1]
id2 <- id[length(id)]
for (i in id1:id2) {
df <- read.csv(x[i], header = TRUE)
df <- data.frame(df)
df <- na.omit(df)
df <- rbind(df)
print(df)
}
# would like a consolidated list of records here to to do more stuff, e.g. filter on pollutant and calcuate mean
}

Answer 1

You can just define the data frame outside the for loop and append to it. Also you can skip some steps in between... There are more ways to improve here... :-)
pmean <- function(directory = "./specdata/", pollutant, id = 1:322) {
x <- list.files(path=directory, pattern="*.csv")
x <- paste(directory, x, sep="")
df_final <- data.frame()
for (i in id) {
df <- read.csv(x[i], header = TRUE)
df <- data.frame(df)
df <- na.omit(df)
df_final <- rbind(df_final, df)
print(df)
}
# would like a consolidated list of records here to to do more stuff, e.g. filter on pollutant and calcuate mean
return(df_final)
}

Answer 2

by only calling df <- rbind(df) you are effectively overwriting df everytime. You can fix this by doing something like this:
df = data.frame() # empty data frame
for(i in 1:10) { # for all you csv files
x <- mean(rnorm(10)) # some new information
df <- rbind(df, x) # bind old dataframe and new value
}
By the way, if you know how big df will be beforehand then this is not the proper way to do it.