newCorrespondenceTable {correspondenceTables}R Documentation

Ex novo creation of candidate correspondence tables between two classifications via pivot tables


Creation of a candidate correspondence table between two classifications, A and B, when there are correspondence tables leading from the first classification to the second one via k intermediate pivot classifications C_1, \ldots, C_k. The correspondence tables leading from A to B are A:C_1, {C_i:C_{i+1}: 1 \le i \le k -1}, B:C_k.


  CSVout = NULL,
  Reference = "none",
  MismatchTolerance = 0.2



A string of type character containing the name of a csv file which contains the names of the files that contain the classifications and the intermediate correspondence tables (see "Details" below).


The preferred name for the output csv files that will contain the candidate correspondence table and information about the classifications involved. The valid values are NULL or strings of type character. If the selected value is NULL, the default, no output file is produced. If the value is a string, then the output is exported into two csv files whose names contain the provided name (see "Value" below).


The reference classification among A and B. If a classification is the reference to the other, and hence hierarchically superior to it, each code of the other classification is expected to be mapped to at most one code of the reference classification. The valid values are "none", "A", and "B". If the selected value is "A" or "B", a "Review" flag column (indicating the records violating this expectation) is included in the output (see "Explanation of the flags" below).


The maximum acceptable proportion of rows in the candidate correspondence table which contain no code for classification A or no code for classification B. The default value is 0.2. The valid values are real numbers in the interval [0, 1].


File and file name requirements:

Classification table requirements:

Correspondence table requirements:

Interdependency requirements:

Mismatch tolerance:

If any of the conditions required from the arguments is violated an error message is produced and execution is stopped.


newCorrespondenceTable() returns a list with two elements, both of which are data frames.

Explanation of the flags

Sample datasets included in the package

Running browseVignettes("correspondenceTables") in the console opens an html page in the user's default browser. Selecting HTML from the menu, users can read information about the use of the sample datasets that are included in the package. If they wish to access the csv files with the sample data, users have two options:


   ## Application of function newCorrespondenceTable() with "example.csv" being the file
   ## that includes the names the files  and the intermediate tables in a sparse square 
   ## matrix containing the 100 rows of the classifications (from ISIC v4 to CPA v2.1 through 
   ## CPC v2.1). The desired name for the csv file that will contain the candidate
   ## correspondence table is "newCorrespondenceTable.csv", the reference classification is 
   ## ISIC v4 ("A") and the maximum acceptable proportion of unmatched codes between
   ## ISIC v4 and CPC v2.1 is 0.56 (this is the minimum mismatch tolerance for the first 100 row 
   ## as 55.5% of the code of ISIC v4 is unmatched).
     A <- read.csv(system.file("extdata", "example.csv", package = "correspondenceTables"), 
                   header = FALSE, 
                   sep = ",")
     for (i in 1:nrow(A)) {
       for (j in 1:ncol(A)) {
         if (A[i,j]!="") {
           A[i, j] <- system.file("extdata", A[i, j], package = "correspondenceTables")
     write.table(x = A, 
                 file = file.path(tmp_dir,"example.csv"), 
                 row.names = FALSE, 
                 col.names = FALSE, 
                 sep = ",")
     csv_files<-list.files(tmp_dir, pattern = ".csv")

[Package correspondenceTables version 0.7.4 Index]