How to Save a Data Frame as CSV to a User Selected Location Using Tcltk

How to save a data frame as CSV to a user selected location using tcltk

Take a look at the write.csv or the write.table functions. You just have to supply the file name the user selects to the file parameter, and the dataframe to the x parameter:

write.csv(x=df, file="myFileName")

How can I export in R

Native R: write.csv(Data_passed_slim, "nn.csv").
See ?write.csv for documentation.

But, for larger datasets I would recommend using data.table::fwrite(). Documentation: https://www.rdocumentation.org/packages/data.table/versions/1.14.0/topics/fwrite

Mean values from multiple csv to data frame

I'd also suggest to use (l)apply... Here's my take:

getMeans <- function(fpath,runfct,
                 target_cols = c(2),
                 sep=",",
                 dec=".",
                 header = T,
                 min_obs_threshold = 3){

f <- list.files(fpath)
fcsv <- f[grepl("\.csv",f)]

fcsv <- paste0(fpath,fcsv)

csv_list <- lapply(fcsv,read.table,sep = sep,
                 dec = dec, header = header)

csv_rows <- sapply(csv_list,nrow)

rel_csv_list <- csv_list[!(csv_rows < min_obs_threshold)]

lapply(rel_csv_list,function(x) colMeans(x[,target_cols]))

 }

Also with that kind of error message, the debugger might be very helpful.
Just run debug(moist.each.mean) and execute the function stepwise.

Split one cell data into two variables before save in csv

Yes. Use tidy's seperate to split a column into segments of an original one:

library(tidyverse)

df <- tibble(
  `Observation time` = c(
    '141102/0000',
    '141103/0000',
    '141104/0000'
  )
)

df %>% separate(
  col = `Observation time`,
  into = c('Date', 'Time'),
  sep = '/'
)

This outputs:

# A tibble: 3 x 2
  Date   Time 
  <chr>  <chr>
1 141102 0000 
2 141103 0000 
3 141104 0000 

Note that the Observation time column is dropped and replaced by Date and Time. If you want, you can convert them back to integer (or something else) via a mutate.

How to import output from R to an Excel File

@iceiceice you could try this

stock_reco<- read.csv("C:\\temp\\Migration.csv")
migrate<-as.matrix(stock_reco)
title<-colnames(migrate)
dt1<-migrate[,3]
dt2<-as.Date(dt1, format= "%d/%m/%Y")
reco1<-migrate[,6]
reco<-as.matrix(reco1)
for (i in 1:4099) {
  if((migrate[i,1]== migrate[i+1,1]) && (migrate[i,2]== migrate[i+1,2]))
    {
       k<-difftime(dt2[i+1],dt2[i],units = "days")
       if((k <=180) && (reco[i] == reco[i+1]))
       d <- rbind(d, data.frame(migrate[i,], migrate[i+1,]))
        }
    }

write.csv(file=fileName, x='d')  

Read csv using gfilebrowse from gWidgets

Here is the script after the improvements. Now it does exactly what I expect it to do. I hope someone finds it useful:

# load functions ####
# download function
f.d <- function(hdf.urls,hdf.names,out.dir){
  for(i in 1:length(hdf.urls)){
    URL      <- hdf.urls  [i]     
    file     <- hdf.names [i]   
    download.file(URL,paste(out.dir,"/",file,sep=""),mode="wb")
  }}

# read csv function
f.csv <- function(x){
  df1 <<- read.csv(x,header=TRUE,sep=",")
  hdf.urls  <<- df1$Online.Access.URLs
  hdf.urls  <<- as.character(hdf.urls)
  hdf.names <<- df1$Producer.Granule.ID
  hdf.names <<- as.character(hdf.names)   
}
# load functions ####

# my.DownloadHDFv2 this one works fine ####
my.DownloadHDF <- function(){
  options(guiToolkit = "tcltk")

  win         <- gwindow("Download HDF with R!", visible = FALSE)
  csv.frame   <- gframe("csv with HDFs names ", container = win)

  a <- gfilebrowse("Upload csv file",cont=csv.frame, 
                   handler=function(h,...){
                     f.csv(svalue(a))                   
  })

  path.frame   <- gframe("Output Directory ", container = win)
  brow         <- gfilebrowse(text = "Select folder...", type = "selectdir",container=path.frame,
                              handler=function(h,...){
                                out.dir      <<- svalue(brow)
                              })

  b <- gbutton(text="Start Download",container = win,
                        handler   = function(h,...){
                          f.d(hdf.urls,hdf.names,out.dir=out.dir)                   
                        })
  visible(win)<-TRUE
}
my.DownloadHDF()
# my.DownloadHDFv2 this one works fine ####

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