R/check_element_mismatch_error.R

In dataquieR: Data Quality in Epidemiological Research

#' Identify data sets element mismatch errors
#'
#' @description
#' At first the intersect of id values of 2 datasets will be achived and if this list length is zero it means that datasets need a concatenation and possible error will be data element error . Otherwise the data record mismatch will be assesed.
#'
#' export
#' @noRd
#'
#' @param d1 [data.frame] first dataframe
#' @param d2 [data.frame] second dataframe
#' @param id [character] identification category name
#' @return A [integer] the output is not clear yet

check_element_mismatch_error <- function(d1, d2, id){

    valuesd1 = as.vector( d1[,c(id)] )
    valuesd2 = as.vector( d2[,c(id)] )
    nrow_d1 = nrow(d1)
    nrow_d2 = nrow(d2)

    dmerged = merge(d1,d2)
    col_merged = names(dmerged)
    col_data1 = names(d1)
    col_data2 = names(d2)

    if (length(col_merged)>length(col_data1)){
        print('Data element mismatch')
        set_c1_min_c2 = list(setdiff(col_data1,col_data2))
        set_c2_min_c1 = list(setdiff(col_data2,col_data1))

        results = list(set_c1_min_c2, set_c2_min_c1)
        #print(c('mismatched columns in input_1: ', set_c1_min_c2))
        #print('"""""""""""""""""""')
        #print(c('mismatched columns in input_2: ', set_c2_min_c1))
    }
    else{
        print('No data element mismatch')
        set_c1_min_c2 = list(NULL)
        set_c2_min_c1 = list(NULL)

        results = list(set_c1_min_c2, set_c2_min_c1)
    }




    return(results)
}