thanks for reporting the issue with the gcc and or g++ version, on my system (standard installtion of Ubuntu 20 LTS) i get these outputs:
thho@kuburock:~$ dpkg --list | grep compiler
ii g++ 4:9.3.0-1ubuntu2 amd64 GNU C++ compiler
ii g++-9 9.3.0-10ubuntu2 amd64 GNU C++ compiler
ii gcc 4:9.3.0-1ubuntu2 amd64 GNU C compiler
ii gcc-9 9.3.0-10ubuntu2 amd64 GNU C compiler
ii gfortran 4:9.3.0-1ubuntu2 amd64 GNU Fortran 95 compiler
ii gfortran-9 9.3.0-10ubuntu2 amd64 GNU Fortran compiler
ii libllvm10:amd64 1:10.0.0-4ubuntu1 amd64 Modular compiler and toolchain technologies, runtime library
ii libllvm10:i386 1:10.0.0-4ubuntu1 i386 Modular compiler and toolchain technologies, runtime library
ii libllvm9:amd64 1:9.0.1-12 amd64 Modular compiler and toolchain technologies, runtime library
ii libparams-validationcompiler-perl 0.30-1 all module to build an optimized subroutine parameter validator
ii libxkbcommon0:amd64 0.10.0-1 amd64 library interface to the XKB compiler - shared library
For me it looks like gcc and g++ is the same on our systems. Anyway, have you tried to make a full new installation of R +RStudio, with the latest version i found it pretty straight forward:
## R and RStudio
sudo apt update
sudo apt -y install r-base gdebi-core
#download the Rstudio *.deb package from the official Rstudio websit
cd Downloads
sudo gdebi rstudio-1.2.5019-amd64.deb
Regarding your question how to subset points after exporting the csv, check this script, where roi.kml are your polygons of the locations you want to extract the points you are interested in.:
###########################
###subset ts plot export###
###########################
library(sp)
library(rgdal)
library(rgeos)
#read subsetpolygon
roi <- readOGR("/home/user/studysite/roi.kml")
#read exported .csv
pnts <- read.csv("/home/user/ISNAR_master_date/stamps_tsexport.csv")
#create spatial object
lon <- pnts$export_res_1[2:nrow(pnts)]
lat <- pnts$export_res_2[2:nrow(pnts)]
loc <- data.frame(lon, lat)
pnts.geo <- SpatialPointsDataFrame(loc, pnts[2:nrow(pnts), ],
proj4string = CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"))
#spatial subset
pnts.sub <- pnts.geo[roi, ]
#create table from spatial subset
sub.csv <- rbind(pnts[1, ], pnts.sub@data)
#export csv to StaMPS-Visualizer application
#adapt path to your machine
write.table(sub.csv, file = "/home/user/stamps_visualizer/stusi/stamps_tsexport.csv",
row.names = F, col.names = T, sep = ",")