es,
Philip
On Mon, 29 Nov 2021 at 00:31, Jeff Newmiller wrote:
>
> This "data_long" appears to be a mess you are not satisfied with, rather than
> the "data" you started with or a model of what you want.
>
> On November 28, 2021 9:06:54 AM PST, Philip
ometimes seen, legalistically correctly I think, as outside the remit of
> this Email list) but I agree
> that the help for pivot_longer() and many other tidyverse functions is not as
> good as it could be particularly
> for people new to R. Often there is better documentation in vignettes
Hello,
I have a wide table that I transform to a long table for analysis.
The wide table has 25 columns - the first is labels, then columns 2:25
are monthly data of LST which is in 19 rows.
I mutate this with :
data_long <- data %>% pivot_longer(cols = 2:25, names_to =
aving 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 Sat, Nov 20, 2021 at 12:23 PM Philip Monk wrote:
> >
> > Thanks, Andrew. I didn't realise as
something like:
> >
> >
> >x <- c("28/10/2016", "19/11/2016", "31/12/2016", "16/01/2016", "05/03/2017")
> >as.Date(x, format = "%d/%m/%Y")
> >
> >
> >which produces this output:
> &
quot;19/11/2016", "31/12/2016", "16/01/2016", "05/03/2017")
> > as.Date(x, format = "%d/%m/%Y")
> [1] "2016-10-28" "2016-11-19" "2016-12-31" "2016-01-16" "2017-03-05"
> >
>
>
> mu
5603507272.3722267991.995863839
On Sat, 20 Nov 2021 at 17:08, Philip Monk wrote:
>
> Hello,
>
> Simple but infuriating problem.
>
> Reading in CSV of data using :
>
> ```
> # CSV file has column headers with date of scene capture in format dd/mm/
> # c
Hello,
Simple but infuriating problem.
Reading in CSV of data using :
```
# CSV file has column headers with date of scene capture in format
dd/mm/
# check.names = FALSE averts R incorrectly processing dates due to '/'
data <- read.csv("C:/R_data/Bungala (b2000) julian.csv", check.names =
FA
Hello,
First post - apologies if I get anything wrong - either in describing the
question (I've only been using R for a week) or etiquette.
I have CSV files of Land Surface Temperature (LST) data derived from
Landsat 8 data and exported from Google Earth Engine. I am investigating
whether the co
A.K.
Thanks for the reply. Will give it a try...
Jac
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Hi All,
I have 1029 *.csv files that I would like read individually into R, delete
some columns and rename others, and then export individually using the
original file names.
I have written some script to do this for an individual file (script below),
but cannot get it to loop through all the fi
thanks a lot , that will do the trick
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dear all,
i have a quite simple question, i want to fill up a Matrix like done in the
following function,
but the performance is very bad for large dimensions
is there a way to do this like with apply or something similar?
makeMatrix <- function(a, b,dim) {
X=matrix(0,ncol=dim,nrow=dim)
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