And just for fun, here is a more "functional" version without the
explicit 'for()' loops that gives the lower triangular values of the
counts of nonmissing values for each correlation:
## (using John's notation)
w <- expand.grid(1:nc,1:nc)
f <- \(x) ifelse(x[1] <= x[2], NA, nrow(na.omit(dat[,x])))
Thank you John for your help and advice.
On Fri, Aug 26, 2022 at 11:04 AM John Fox wrote:
>
> Dear Val,
>
> On 2022-08-26 10:41 a.m., Val wrote:
> > Hi John and Timothy
> >
> > Thank you for your suggestion and help. Using the sample data, I did
> > carry out a test run and found a difference in
Hello,
You are right, I haven't assigned the return value.
Start the pipe with something like
RiverTweed <- page |>
rest_of_pipe
If you have more files to download and process, post an example of 2 or
3 links and I'll see if it can be automated.
Also posting to R-help.
Hope this helps,
Sorry, there's simpler code. I used html_elements (plural) and the
result is a list. Use html_element (singular) and the output is a tibble.
page |>
html_element("table") |>
html_table(header = TRUE) |>
(\(x) {
hdr <- unlist(x[3, ])
y <- x[-(1:3), ]
names(y) <- hdr
y
})(
Hello,
You can try the following. It worked with me.
Read from the link and post-process the html data extracting the element
"table" and then the table itself.
This table has 3 rows before the actual table so the lapply below will
get the table and its header.
library(httr)
library(rvest)
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