Are these files of numerics? In other words, how would one know whether the
first line of a file of alpha data are headers or not? read.table's Help
file contains some info that may or may not be relevant for your files also.
Assuming a criterion for distinction, one could simply read the first line
of a file, check the criterion, and then read it with or without headers as
appropriate. R can create default column names. One could also use
readLines with connections, but I don't think this is necessary, though
maybe it's more elegant or faster.
Without knowing how to tell whether the first line is a header or not, I
have no clue. Maybe the filename/ suffix might tell you something.
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Tue, Aug 13, 2019 at 11:00 AM Christopher W Ryan <cr...@binghamton.edu>
wrote:
> Alas, we spend so much time and energy on data wrangling . . . .
>
> I'm given a collection of csv files to work with---"found data". They arose
> via saving Excel files to csv format. They all have the same column
> structure, except that some were saved with column names and some were not.
>
> I have a code snippet that I've used before to traverse a directory and
> read into R all the csv files of a certain filename pattern within it, and
> combine them all into a single dataframe:
>
> library(dplyr)
> ## specify the csv files that I will want to access
> files.to.read <- list.files(path = "H:/EH", pattern =
> "WICLeadLabOrdersDone.+", all.files = FALSE, full.names = TRUE, recursive =
> FALSE, ignore.case = FALSE, include.dirs = FALSE, no.. = FALSE)
>
> ## function to read csv files back in
> read.csv.files <- function(filename) {
> bb <- read.csv(filename, colClasses = "character", header = TRUE)
> bb
> }
>
> ## now read the csv files, as all character
> b <- lapply(files.to.read, read.csv.files)
>
> ddd <- bind_rows(b)
>
> But this assumes that all files have column names in their first row. In
> this case, some don't. Any advice how to handle it so that those with
> column names and those without are read in and combined properly? The only
> thing I've come up with so far is:
>
> ## function to read csv files back in
> ## Unfortunately, some of the csv files are saved with column headers, and
> some are saved without them.
> ## This presents a problem when defining the function to read them: header
> = TRUE or header = FALSE?
> ## The best solution I can think of as of 13 August 2019 is to use header =
> FALSE and skip the
> ## first row of every file. This will sacrifice one record from each csv of
> about 80 files
> read.csv.files <- function(filename) {
> bb <- read.csv(filename, colClasses = "character", header = FALSE, skip
> = 1)
> bb
> }
>
> This sacrifices about 80 out of about 1600 records. For my purposes in this
> instance, this may be acceptable, but of course I'd rather not.
>
> Thanks.
>
> --Chris Ryan
>
> [[alternative HTML version deleted]]
>
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