Combining multifiles and add unique ID for each of them












0















I am newbie in R. I got a problem when combining data, hope that someone help to resolve it.
Suppose that I have two CSV files such as A.csv and B.csv are located at the path "C:UsersPublicA".
They look like that:



A.csv



T,2015,2016,2017,2018
X1,1,2,3,2
X2,1,2,2,3
X3,1,3,4,2



B.csv



T,2015,2016,2017
X1,2,4,3
X2,2,2,3
X3,3,3,4



And then I try to combine them as well as transpose them with following functions. They are created by Ricardo Oliveros-Ramos at here and by Tony Cookson at here.
1. Firstly, I create function read.tcsv to read and transpose data in CSV file



  read.tcsv = function(file, header=TRUE, sep=",", ...) {
n = max(count.fields(file, sep=sep), na.rm=TRUE)
x = readLines(file)

.splitvar = function(x, sep, n) {
var = unlist(strsplit(x, split=sep))
length(var) = n
return(var)
}

x = do.call(cbind, lapply(x, .splitvar, sep=sep, n=n))
x = apply(x, 1, paste, collapse=sep)
out = read.csv(text=x, sep=sep, header=header, ...)
return(out)

}


2. Then I use multrbind.fill to combine and fill missing value



multrbind.fill = function(mypath){
filenames=list.files(path=mypath, full.names=TRUE)
datalist = lapply(filenames, function(x){
read.tcsv(file=x,header=T)
}
)
Reduce(function(x,y) {plyr::rbind.fill(x,y)}, datalist)
}



  1. The result looks good:


ï..T X1 X2 X3
2015 1 1 1
2016 2 2 3
2017 3 2 4
2018 2 3 2
2015 2 2 3
2016 4 2 3
2017 3 3 4




  1. However, I want to add a column as an identifier for each file with their file name (or unique IDs) like that:


ï..T ID X1 X2 X3
2015 A 1 1 1
2016 A 2 2 3
2017 A 3 2 4
2018 A 2 3 2
2015 B 2 2 3
2016 B 4 2 3
2017 B 3 3 4



Someone help me!? Thanks in advance.










share|improve this question





























    0















    I am newbie in R. I got a problem when combining data, hope that someone help to resolve it.
    Suppose that I have two CSV files such as A.csv and B.csv are located at the path "C:UsersPublicA".
    They look like that:



    A.csv



    T,2015,2016,2017,2018
    X1,1,2,3,2
    X2,1,2,2,3
    X3,1,3,4,2



    B.csv



    T,2015,2016,2017
    X1,2,4,3
    X2,2,2,3
    X3,3,3,4



    And then I try to combine them as well as transpose them with following functions. They are created by Ricardo Oliveros-Ramos at here and by Tony Cookson at here.
    1. Firstly, I create function read.tcsv to read and transpose data in CSV file



      read.tcsv = function(file, header=TRUE, sep=",", ...) {
    n = max(count.fields(file, sep=sep), na.rm=TRUE)
    x = readLines(file)

    .splitvar = function(x, sep, n) {
    var = unlist(strsplit(x, split=sep))
    length(var) = n
    return(var)
    }

    x = do.call(cbind, lapply(x, .splitvar, sep=sep, n=n))
    x = apply(x, 1, paste, collapse=sep)
    out = read.csv(text=x, sep=sep, header=header, ...)
    return(out)

    }


    2. Then I use multrbind.fill to combine and fill missing value



    multrbind.fill = function(mypath){
    filenames=list.files(path=mypath, full.names=TRUE)
    datalist = lapply(filenames, function(x){
    read.tcsv(file=x,header=T)
    }
    )
    Reduce(function(x,y) {plyr::rbind.fill(x,y)}, datalist)
    }



    1. The result looks good:


    ï..T X1 X2 X3
    2015 1 1 1
    2016 2 2 3
    2017 3 2 4
    2018 2 3 2
    2015 2 2 3
    2016 4 2 3
    2017 3 3 4




    1. However, I want to add a column as an identifier for each file with their file name (or unique IDs) like that:


    ï..T ID X1 X2 X3
    2015 A 1 1 1
    2016 A 2 2 3
    2017 A 3 2 4
    2018 A 2 3 2
    2015 B 2 2 3
    2016 B 4 2 3
    2017 B 3 3 4



    Someone help me!? Thanks in advance.










    share|improve this question



























      0












      0








      0








      I am newbie in R. I got a problem when combining data, hope that someone help to resolve it.
      Suppose that I have two CSV files such as A.csv and B.csv are located at the path "C:UsersPublicA".
      They look like that:



      A.csv



      T,2015,2016,2017,2018
      X1,1,2,3,2
      X2,1,2,2,3
      X3,1,3,4,2



      B.csv



      T,2015,2016,2017
      X1,2,4,3
      X2,2,2,3
      X3,3,3,4



      And then I try to combine them as well as transpose them with following functions. They are created by Ricardo Oliveros-Ramos at here and by Tony Cookson at here.
      1. Firstly, I create function read.tcsv to read and transpose data in CSV file



        read.tcsv = function(file, header=TRUE, sep=",", ...) {
      n = max(count.fields(file, sep=sep), na.rm=TRUE)
      x = readLines(file)

      .splitvar = function(x, sep, n) {
      var = unlist(strsplit(x, split=sep))
      length(var) = n
      return(var)
      }

      x = do.call(cbind, lapply(x, .splitvar, sep=sep, n=n))
      x = apply(x, 1, paste, collapse=sep)
      out = read.csv(text=x, sep=sep, header=header, ...)
      return(out)

      }


      2. Then I use multrbind.fill to combine and fill missing value



      multrbind.fill = function(mypath){
      filenames=list.files(path=mypath, full.names=TRUE)
      datalist = lapply(filenames, function(x){
      read.tcsv(file=x,header=T)
      }
      )
      Reduce(function(x,y) {plyr::rbind.fill(x,y)}, datalist)
      }



      1. The result looks good:


      ï..T X1 X2 X3
      2015 1 1 1
      2016 2 2 3
      2017 3 2 4
      2018 2 3 2
      2015 2 2 3
      2016 4 2 3
      2017 3 3 4




      1. However, I want to add a column as an identifier for each file with their file name (or unique IDs) like that:


      ï..T ID X1 X2 X3
      2015 A 1 1 1
      2016 A 2 2 3
      2017 A 3 2 4
      2018 A 2 3 2
      2015 B 2 2 3
      2016 B 4 2 3
      2017 B 3 3 4



      Someone help me!? Thanks in advance.










      share|improve this question
















      I am newbie in R. I got a problem when combining data, hope that someone help to resolve it.
      Suppose that I have two CSV files such as A.csv and B.csv are located at the path "C:UsersPublicA".
      They look like that:



      A.csv



      T,2015,2016,2017,2018
      X1,1,2,3,2
      X2,1,2,2,3
      X3,1,3,4,2



      B.csv



      T,2015,2016,2017
      X1,2,4,3
      X2,2,2,3
      X3,3,3,4



      And then I try to combine them as well as transpose them with following functions. They are created by Ricardo Oliveros-Ramos at here and by Tony Cookson at here.
      1. Firstly, I create function read.tcsv to read and transpose data in CSV file



        read.tcsv = function(file, header=TRUE, sep=",", ...) {
      n = max(count.fields(file, sep=sep), na.rm=TRUE)
      x = readLines(file)

      .splitvar = function(x, sep, n) {
      var = unlist(strsplit(x, split=sep))
      length(var) = n
      return(var)
      }

      x = do.call(cbind, lapply(x, .splitvar, sep=sep, n=n))
      x = apply(x, 1, paste, collapse=sep)
      out = read.csv(text=x, sep=sep, header=header, ...)
      return(out)

      }


      2. Then I use multrbind.fill to combine and fill missing value



      multrbind.fill = function(mypath){
      filenames=list.files(path=mypath, full.names=TRUE)
      datalist = lapply(filenames, function(x){
      read.tcsv(file=x,header=T)
      }
      )
      Reduce(function(x,y) {plyr::rbind.fill(x,y)}, datalist)
      }



      1. The result looks good:


      ï..T X1 X2 X3
      2015 1 1 1
      2016 2 2 3
      2017 3 2 4
      2018 2 3 2
      2015 2 2 3
      2016 4 2 3
      2017 3 3 4




      1. However, I want to add a column as an identifier for each file with their file name (or unique IDs) like that:


      ï..T ID X1 X2 X3
      2015 A 1 1 1
      2016 A 2 2 3
      2017 A 3 2 4
      2018 A 2 3 2
      2015 B 2 2 3
      2016 B 4 2 3
      2017 B 3 3 4



      Someone help me!? Thanks in advance.







      r csv dataframe






      share|improve this question















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      edited Nov 23 '18 at 21:19







      Vĩnh Vũ Quang

















      asked Nov 23 '18 at 14:15









      Vĩnh Vũ QuangVĩnh Vũ Quang

      112




      112
























          2 Answers
          2






          active

          oldest

          votes


















          1














          Thanks TJ83 for helping me to correct the function. Base on TJ83's comments, I add an identifier column named ID. And here is my complete function read.tcsv



          read.tcsv = function(file, header=TRUE, sep=",", ...) {
          n = max(count.fields(file, sep=sep), na.rm=TRUE)
          x = readLines(file)

          .splitvar = function(x, sep, n) {
          var = unlist(strsplit(x, split=sep))
          length(var) = n
          return(var)
          }

          x = do.call(cbind, lapply(x, .splitvar, sep=sep, n=n))
          x = apply(x, 1, paste, collapse=sep)

          out = read.csv(text=x, sep=sep, header=header, ...)
          out$ID<-tools::file_path_sans_ext(basename(file))
          return(out)

          }





          share|improve this answer































            0














            1) If you only have 2 datasets, then the fastest way would be to add an ID-column on A and B datasets after transformation but before binding the rows.



            Dataset_A$ID<-"A"
            Dataset_B$ID<-"B"
            # Where Dataset_X is the name of your imported transformed datasets.


            2) Could you show your exact code used? If you only have 2 datasets I think the code you have created could be simplified substantially. If you are interested in a simplification then please supply us with output from the 2 dput-statements below:



            A<-read.csv("A-dataset")
            B<-read.csv("B-dataset")
            dput(A)
            dput(B)





            share|improve this answer
























            • In fact, I have more than 350 CSV files in folder A, so I have to use function multrbind.fill to combine all of them at once.

              – Vĩnh Vũ Quang
              Nov 23 '18 at 21:15











            • I call name of these files by tools with file_path_sans_ext(list.files(file.path(mypath))). But, I do not know how to add it into the data frame properly.

              – Vĩnh Vũ Quang
              Nov 24 '18 at 0:34













            • Here is the output of my result: dput(multirbind("C:/Users/Vu Quang Vinh/Desktop/A")) structure(list(ï..T = c(2015L, 2016L, 2017L, 2018L, 2015L, 2016L, 2017L), X1 = c(1L, 2L, 3L, 2L, 2L, 4L, 3L), X2 = c(1L, 2L, 2L, 3L, 2L, 2L, 3L), X3 = c(1L, 3L, 4L, 2L, 3L, 3L, 4L)), class = "data.frame", row.names = c(NA, -7L))

              – Vĩnh Vũ Quang
              Nov 24 '18 at 1:23













            • When you do it all in one step and I don't have access to the csv-files, it is very difficult to reproduce. read.tcsv(file=x,header=T) } Between the 2 lines you should add something like x$ID<-paste(x)

              – TJ83
              Nov 24 '18 at 1:36













            • You can create 2 CSV files like A.csv and B.csv that I mentioned above. And then using read.tcsv as well as mulrbind.fill to reproduce the result. I also tried your suggestion but it doesn't work :(.

              – Vĩnh Vũ Quang
              Nov 24 '18 at 2:26











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            2 Answers
            2






            active

            oldest

            votes








            2 Answers
            2






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            1














            Thanks TJ83 for helping me to correct the function. Base on TJ83's comments, I add an identifier column named ID. And here is my complete function read.tcsv



            read.tcsv = function(file, header=TRUE, sep=",", ...) {
            n = max(count.fields(file, sep=sep), na.rm=TRUE)
            x = readLines(file)

            .splitvar = function(x, sep, n) {
            var = unlist(strsplit(x, split=sep))
            length(var) = n
            return(var)
            }

            x = do.call(cbind, lapply(x, .splitvar, sep=sep, n=n))
            x = apply(x, 1, paste, collapse=sep)

            out = read.csv(text=x, sep=sep, header=header, ...)
            out$ID<-tools::file_path_sans_ext(basename(file))
            return(out)

            }





            share|improve this answer




























              1














              Thanks TJ83 for helping me to correct the function. Base on TJ83's comments, I add an identifier column named ID. And here is my complete function read.tcsv



              read.tcsv = function(file, header=TRUE, sep=",", ...) {
              n = max(count.fields(file, sep=sep), na.rm=TRUE)
              x = readLines(file)

              .splitvar = function(x, sep, n) {
              var = unlist(strsplit(x, split=sep))
              length(var) = n
              return(var)
              }

              x = do.call(cbind, lapply(x, .splitvar, sep=sep, n=n))
              x = apply(x, 1, paste, collapse=sep)

              out = read.csv(text=x, sep=sep, header=header, ...)
              out$ID<-tools::file_path_sans_ext(basename(file))
              return(out)

              }





              share|improve this answer


























                1












                1








                1







                Thanks TJ83 for helping me to correct the function. Base on TJ83's comments, I add an identifier column named ID. And here is my complete function read.tcsv



                read.tcsv = function(file, header=TRUE, sep=",", ...) {
                n = max(count.fields(file, sep=sep), na.rm=TRUE)
                x = readLines(file)

                .splitvar = function(x, sep, n) {
                var = unlist(strsplit(x, split=sep))
                length(var) = n
                return(var)
                }

                x = do.call(cbind, lapply(x, .splitvar, sep=sep, n=n))
                x = apply(x, 1, paste, collapse=sep)

                out = read.csv(text=x, sep=sep, header=header, ...)
                out$ID<-tools::file_path_sans_ext(basename(file))
                return(out)

                }





                share|improve this answer













                Thanks TJ83 for helping me to correct the function. Base on TJ83's comments, I add an identifier column named ID. And here is my complete function read.tcsv



                read.tcsv = function(file, header=TRUE, sep=",", ...) {
                n = max(count.fields(file, sep=sep), na.rm=TRUE)
                x = readLines(file)

                .splitvar = function(x, sep, n) {
                var = unlist(strsplit(x, split=sep))
                length(var) = n
                return(var)
                }

                x = do.call(cbind, lapply(x, .splitvar, sep=sep, n=n))
                x = apply(x, 1, paste, collapse=sep)

                out = read.csv(text=x, sep=sep, header=header, ...)
                out$ID<-tools::file_path_sans_ext(basename(file))
                return(out)

                }






                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 24 '18 at 6:46









                Vĩnh Vũ QuangVĩnh Vũ Quang

                112




                112

























                    0














                    1) If you only have 2 datasets, then the fastest way would be to add an ID-column on A and B datasets after transformation but before binding the rows.



                    Dataset_A$ID<-"A"
                    Dataset_B$ID<-"B"
                    # Where Dataset_X is the name of your imported transformed datasets.


                    2) Could you show your exact code used? If you only have 2 datasets I think the code you have created could be simplified substantially. If you are interested in a simplification then please supply us with output from the 2 dput-statements below:



                    A<-read.csv("A-dataset")
                    B<-read.csv("B-dataset")
                    dput(A)
                    dput(B)





                    share|improve this answer
























                    • In fact, I have more than 350 CSV files in folder A, so I have to use function multrbind.fill to combine all of them at once.

                      – Vĩnh Vũ Quang
                      Nov 23 '18 at 21:15











                    • I call name of these files by tools with file_path_sans_ext(list.files(file.path(mypath))). But, I do not know how to add it into the data frame properly.

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 0:34













                    • Here is the output of my result: dput(multirbind("C:/Users/Vu Quang Vinh/Desktop/A")) structure(list(ï..T = c(2015L, 2016L, 2017L, 2018L, 2015L, 2016L, 2017L), X1 = c(1L, 2L, 3L, 2L, 2L, 4L, 3L), X2 = c(1L, 2L, 2L, 3L, 2L, 2L, 3L), X3 = c(1L, 3L, 4L, 2L, 3L, 3L, 4L)), class = "data.frame", row.names = c(NA, -7L))

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 1:23













                    • When you do it all in one step and I don't have access to the csv-files, it is very difficult to reproduce. read.tcsv(file=x,header=T) } Between the 2 lines you should add something like x$ID<-paste(x)

                      – TJ83
                      Nov 24 '18 at 1:36













                    • You can create 2 CSV files like A.csv and B.csv that I mentioned above. And then using read.tcsv as well as mulrbind.fill to reproduce the result. I also tried your suggestion but it doesn't work :(.

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 2:26
















                    0














                    1) If you only have 2 datasets, then the fastest way would be to add an ID-column on A and B datasets after transformation but before binding the rows.



                    Dataset_A$ID<-"A"
                    Dataset_B$ID<-"B"
                    # Where Dataset_X is the name of your imported transformed datasets.


                    2) Could you show your exact code used? If you only have 2 datasets I think the code you have created could be simplified substantially. If you are interested in a simplification then please supply us with output from the 2 dput-statements below:



                    A<-read.csv("A-dataset")
                    B<-read.csv("B-dataset")
                    dput(A)
                    dput(B)





                    share|improve this answer
























                    • In fact, I have more than 350 CSV files in folder A, so I have to use function multrbind.fill to combine all of them at once.

                      – Vĩnh Vũ Quang
                      Nov 23 '18 at 21:15











                    • I call name of these files by tools with file_path_sans_ext(list.files(file.path(mypath))). But, I do not know how to add it into the data frame properly.

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 0:34













                    • Here is the output of my result: dput(multirbind("C:/Users/Vu Quang Vinh/Desktop/A")) structure(list(ï..T = c(2015L, 2016L, 2017L, 2018L, 2015L, 2016L, 2017L), X1 = c(1L, 2L, 3L, 2L, 2L, 4L, 3L), X2 = c(1L, 2L, 2L, 3L, 2L, 2L, 3L), X3 = c(1L, 3L, 4L, 2L, 3L, 3L, 4L)), class = "data.frame", row.names = c(NA, -7L))

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 1:23













                    • When you do it all in one step and I don't have access to the csv-files, it is very difficult to reproduce. read.tcsv(file=x,header=T) } Between the 2 lines you should add something like x$ID<-paste(x)

                      – TJ83
                      Nov 24 '18 at 1:36













                    • You can create 2 CSV files like A.csv and B.csv that I mentioned above. And then using read.tcsv as well as mulrbind.fill to reproduce the result. I also tried your suggestion but it doesn't work :(.

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 2:26














                    0












                    0








                    0







                    1) If you only have 2 datasets, then the fastest way would be to add an ID-column on A and B datasets after transformation but before binding the rows.



                    Dataset_A$ID<-"A"
                    Dataset_B$ID<-"B"
                    # Where Dataset_X is the name of your imported transformed datasets.


                    2) Could you show your exact code used? If you only have 2 datasets I think the code you have created could be simplified substantially. If you are interested in a simplification then please supply us with output from the 2 dput-statements below:



                    A<-read.csv("A-dataset")
                    B<-read.csv("B-dataset")
                    dput(A)
                    dput(B)





                    share|improve this answer













                    1) If you only have 2 datasets, then the fastest way would be to add an ID-column on A and B datasets after transformation but before binding the rows.



                    Dataset_A$ID<-"A"
                    Dataset_B$ID<-"B"
                    # Where Dataset_X is the name of your imported transformed datasets.


                    2) Could you show your exact code used? If you only have 2 datasets I think the code you have created could be simplified substantially. If you are interested in a simplification then please supply us with output from the 2 dput-statements below:



                    A<-read.csv("A-dataset")
                    B<-read.csv("B-dataset")
                    dput(A)
                    dput(B)






                    share|improve this answer












                    share|improve this answer



                    share|improve this answer










                    answered Nov 23 '18 at 16:37









                    TJ83TJ83

                    614




                    614













                    • In fact, I have more than 350 CSV files in folder A, so I have to use function multrbind.fill to combine all of them at once.

                      – Vĩnh Vũ Quang
                      Nov 23 '18 at 21:15











                    • I call name of these files by tools with file_path_sans_ext(list.files(file.path(mypath))). But, I do not know how to add it into the data frame properly.

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 0:34













                    • Here is the output of my result: dput(multirbind("C:/Users/Vu Quang Vinh/Desktop/A")) structure(list(ï..T = c(2015L, 2016L, 2017L, 2018L, 2015L, 2016L, 2017L), X1 = c(1L, 2L, 3L, 2L, 2L, 4L, 3L), X2 = c(1L, 2L, 2L, 3L, 2L, 2L, 3L), X3 = c(1L, 3L, 4L, 2L, 3L, 3L, 4L)), class = "data.frame", row.names = c(NA, -7L))

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 1:23













                    • When you do it all in one step and I don't have access to the csv-files, it is very difficult to reproduce. read.tcsv(file=x,header=T) } Between the 2 lines you should add something like x$ID<-paste(x)

                      – TJ83
                      Nov 24 '18 at 1:36













                    • You can create 2 CSV files like A.csv and B.csv that I mentioned above. And then using read.tcsv as well as mulrbind.fill to reproduce the result. I also tried your suggestion but it doesn't work :(.

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 2:26



















                    • In fact, I have more than 350 CSV files in folder A, so I have to use function multrbind.fill to combine all of them at once.

                      – Vĩnh Vũ Quang
                      Nov 23 '18 at 21:15











                    • I call name of these files by tools with file_path_sans_ext(list.files(file.path(mypath))). But, I do not know how to add it into the data frame properly.

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 0:34













                    • Here is the output of my result: dput(multirbind("C:/Users/Vu Quang Vinh/Desktop/A")) structure(list(ï..T = c(2015L, 2016L, 2017L, 2018L, 2015L, 2016L, 2017L), X1 = c(1L, 2L, 3L, 2L, 2L, 4L, 3L), X2 = c(1L, 2L, 2L, 3L, 2L, 2L, 3L), X3 = c(1L, 3L, 4L, 2L, 3L, 3L, 4L)), class = "data.frame", row.names = c(NA, -7L))

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 1:23













                    • When you do it all in one step and I don't have access to the csv-files, it is very difficult to reproduce. read.tcsv(file=x,header=T) } Between the 2 lines you should add something like x$ID<-paste(x)

                      – TJ83
                      Nov 24 '18 at 1:36













                    • You can create 2 CSV files like A.csv and B.csv that I mentioned above. And then using read.tcsv as well as mulrbind.fill to reproduce the result. I also tried your suggestion but it doesn't work :(.

                      – Vĩnh Vũ Quang
                      Nov 24 '18 at 2:26

















                    In fact, I have more than 350 CSV files in folder A, so I have to use function multrbind.fill to combine all of them at once.

                    – Vĩnh Vũ Quang
                    Nov 23 '18 at 21:15





                    In fact, I have more than 350 CSV files in folder A, so I have to use function multrbind.fill to combine all of them at once.

                    – Vĩnh Vũ Quang
                    Nov 23 '18 at 21:15













                    I call name of these files by tools with file_path_sans_ext(list.files(file.path(mypath))). But, I do not know how to add it into the data frame properly.

                    – Vĩnh Vũ Quang
                    Nov 24 '18 at 0:34







                    I call name of these files by tools with file_path_sans_ext(list.files(file.path(mypath))). But, I do not know how to add it into the data frame properly.

                    – Vĩnh Vũ Quang
                    Nov 24 '18 at 0:34















                    Here is the output of my result: dput(multirbind("C:/Users/Vu Quang Vinh/Desktop/A")) structure(list(ï..T = c(2015L, 2016L, 2017L, 2018L, 2015L, 2016L, 2017L), X1 = c(1L, 2L, 3L, 2L, 2L, 4L, 3L), X2 = c(1L, 2L, 2L, 3L, 2L, 2L, 3L), X3 = c(1L, 3L, 4L, 2L, 3L, 3L, 4L)), class = "data.frame", row.names = c(NA, -7L))

                    – Vĩnh Vũ Quang
                    Nov 24 '18 at 1:23







                    Here is the output of my result: dput(multirbind("C:/Users/Vu Quang Vinh/Desktop/A")) structure(list(ï..T = c(2015L, 2016L, 2017L, 2018L, 2015L, 2016L, 2017L), X1 = c(1L, 2L, 3L, 2L, 2L, 4L, 3L), X2 = c(1L, 2L, 2L, 3L, 2L, 2L, 3L), X3 = c(1L, 3L, 4L, 2L, 3L, 3L, 4L)), class = "data.frame", row.names = c(NA, -7L))

                    – Vĩnh Vũ Quang
                    Nov 24 '18 at 1:23















                    When you do it all in one step and I don't have access to the csv-files, it is very difficult to reproduce. read.tcsv(file=x,header=T) } Between the 2 lines you should add something like x$ID<-paste(x)

                    – TJ83
                    Nov 24 '18 at 1:36







                    When you do it all in one step and I don't have access to the csv-files, it is very difficult to reproduce. read.tcsv(file=x,header=T) } Between the 2 lines you should add something like x$ID<-paste(x)

                    – TJ83
                    Nov 24 '18 at 1:36















                    You can create 2 CSV files like A.csv and B.csv that I mentioned above. And then using read.tcsv as well as mulrbind.fill to reproduce the result. I also tried your suggestion but it doesn't work :(.

                    – Vĩnh Vũ Quang
                    Nov 24 '18 at 2:26





                    You can create 2 CSV files like A.csv and B.csv that I mentioned above. And then using read.tcsv as well as mulrbind.fill to reproduce the result. I also tried your suggestion but it doesn't work :(.

                    – Vĩnh Vũ Quang
                    Nov 24 '18 at 2:26


















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