Take a look at the "Estimated Global Trend daily values" file on this NOAA web page. It is a .txt file with something like 50 header lines (identified with leading #s) followed by several thousand lines of tabular data. The link to download the file is embedded in the code below.
How can I read this file so that I end up with a data frame (or tibble) with the appropriate column names and data?
All the text-to-data functions I know get stymied by those header lines. Here's what I just tried, riffing off of this SO Q&A. My thought was to read the file into a list of lines, then drop the lines that start with # from the list, then do.call(rbind, ...) the rest. The downloading part at the top works fine, but when I run the function, I'm getting back an empty list.
temp <- paste0(tempfile(), ".txt")
download.file("ftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_trend_gl.txt",
destfile = temp, mode = "wb")
processFile = function(filepath) {
dat_list <- list()
con = file(filepath, "r")
while ( TRUE ) {
line = readLines(con, n = 1)
if ( length(line) == 0 ) {
break
}
append(dat_list, line)
}
close(con)
return(dat_list)
}
dat_list <- processFile(temp)