Thanks, Calum. After rereading the post, I came to your interpret it
as you did. So glad that we agree.
"easier" of course is in the mind of the beholder. But I'm glad that
you presented a "tidyverse" approach. There are other issues of
dependencies and efficiency that also might be relevant.
Any
Bert
I thought she meant she wanted to replace the NAs with the 6. But I could
be wrong.
It looks like the data is combined from cbind.
I'm going to give tidyverse examples because it's (/s) *"always"* (/s)
easier.
require(tidyverse)
# impute the missing NAs
myData <- cbind(VB1d[,1],s1id[,1])
Sorry, not clear to me.
For group 8 in your example, do you want extract the values in column
1 that are not NA, i.e. one value, 6; or do you want to extract the
number of values -- that is, the count -- that are not NA, i.e. 1?
... and for group 5, would it be c(9,9) for the values; or 2 for th
Dear Contributors,
I have a problem with a database composed of many individuals for many
periods, for which I need to perform a manipulation of data as follows.
Here I report the procedure I need to do for the first 32 observations of
the first period.
cbind(VB1d[,1],s1id[,1])
[,1] [,2]
[
В Mon, 26 Aug 2024 14:33:02 +0200
SIBYLLE STÖCKLI via R-help пишет:
> > # Extract raster values within the shapefile
> > extracted_values <- extract(raster_file, shape_file)
> > # Assuming the shapefile has multiple polygons and you want to
> > # create a boxplot for each
> > data_list <- lapply
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