Richard,
I currently have no problem with running out of memory. I was referring to
people who have said they use LARGE structures and I am pointing out how they
can temporarily get way larger even when not expected. Functions that
temporarily will balloon up might come with notifications. A
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 Monk wrote:
>Thanks for your suggestions, Chris.
>
>I'm writing from Gmail's web client, and have checked the message
Thanks for your suggestions, Chris.
I'm writing from Gmail's web client, and have checked the message is
being sent as plain text (though I also did this previously so it may
be that I need to change to Outlook). Let me know if it doesn't work.
Hopefully I've used dput properly (see example belo
Sighh...
Questions on "non-standard" packages such as the TidyVerse universe
are off topic here: per the posting guide:
"If the question relates to a contributed package , e.g., one
downloaded from CRAN, try contacting the package maintainer first. You
can also use find("functionname") and
packag
Often the issue is that different variables in the wide format are of different
types so won't simply
pivot_longer without you making decisions which the function shouldn't make for
you. However, I think
the error messages when that happens are fairly clear so perhaps that's not
what's happeni
Hi!
If I understood this correctly, you want to pivot the columns from 2 to
25 and use the first column as a "key". Your data has 27 columns in
total, right?
I tested it with your data and seems that the parameter 'cols' does
have some problems. It takes all variables irrespectively of the range
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 =
> Have anybody used this module?
> https://cran.r-project.org/web/packages/rredis/README.html
>
> Could share your experience please. thank you.
I have successfully used this package (on Linux and macOS) and I think
it is a great way of storing hashed data across different platforms
and programmin
If you have enough data that running out of memory is a serious problem,
then a language like R or Python or Octave or Matlab that offers you NO
control over storage may not be the best choice. You might need to
consider Julia or even Rust.
However, if you have enough data that running out of mem
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