R/crosstab.R

Defines functions preprocess_multidimensional_tables add_marginals crosstab

Documented in add_marginals crosstab preprocess_multidimensional_tables

#' Function for creating a crosstabs
#'
#' This function creates crosstabs in a flexible manner.
#' @param data Data frame to be analyzed
#' @param formula  A formula for the table with a single row column on the left and column variables in the right
#' @param row.vars A single or vector of row variables, quoted. These are appended to any row variable from formula.
#' @param col.vars A single or vector of column variables, quoted. These are appended to any column variables from formula.
#' @param format  "freq", "col_percent", "row_percent", "total_percent"
#' @param useNa  "ifany", "no", "always"
#' @param title  string Title to be used for printing
#' @param row.margin.format  "percent" to show row percents, "freq" to show row frequency, "none" for no margin
#' @param col.margin.format "percent" to show percents, "freq" to show column frequencies, "none" for no margin
#' @param dnames vector Dimension names to replace the variable names.
#' @param pretty.pring logical TRUE means to add linebreaks for printing with Pander or another package.
#' @keywords crosstab
#' @export

crosstab<-function(data, formula = NULL,
                    row.vars = "",
                    col.vars = "",
                    format = "freq",
                    useNA = "ifany",
                    title = "",
                    row.margin.format = "none",
                    col.margin.format = "freq",
                    dnames = "",
                    pretty.print = FALSE
                    ){

    if (!is.null(formula)){
        formula_variables <- all.vars(formula)
        formula_row <- ifelse(length(formula) == 3 & formula[[3]] == 1,  formula_variables[1], as.character(formula[[2]]))

        if (formula_row == 1 ){
            formula_column <- formula_variables[1:length(formula_variables)]
        } else {
            formula_column <- formula_variables[2:length(formula_variables)]
        }

        # We need to combine the formula variables with any additional variables and also handle formulas with only one variable.
        if(row.vars == "" && formula_row != 1 ){
            row.vars <- formula_row
        } else if (row.vars != "" && formula_row != 1) {
            row.vars <- c(formula_row, row.vars)
        }

        if (col.vars == "" && !is.na(formula_column)){
            col.vars <- formula_column
        } else if (col.vars != "" && !is.na(formula_column)) {
            col.vars <- c(formula_column, col.vars)
        }
    }

    factorsToUse <- c(row.vars, col.vars)

    # Deal with case where row.vars or col.vars is empty.
    factorsToUse <- factorsToUse[factorsToUse != ""]
    nvars <- length(factorsToUse)
    if (nvars == 0 ){
        return("No variables were specified")
    }

    if (nvars == 1 && col.vars == "") {
        # In this case for now we are just returing the one column frequency table
        onedtable <- lehmansociology::frequency(data[factorsToUse])
        return(onedtable)
    }

    # Deal with spaces in variable name, but make it backward compatible.
    if (grepl(" ", factorsToUse) == TRUE && substr(factorsToUse, 1, 1) != "`") {
            factorsToUse<-paste0("`",factorsToUse,"`")
        } else {
            factorsToUse <- factorsToUse
        }

    form <- as.formula(paste(" ~", paste(factorsToUse, collapse="+"), sep=""))

    tab <- xtabs( form, data = data)

    if (length(factorsToUse) > 2) {
       tab <- preprocess_multidimensional_tables(tab, row.vars, col.vars, pretty.print, nvars)
    }

    # Now process everything as though it is a two way table.
    tabn<-margin.table(tab)

    margin.row.f <- margin.table(tab,1)
    margin.row.p <- prop.table(margin.row.f)

    if (row.vars != ""){
         margin.col.f <-  margin.table(tab,2)
         margin.col.p <-  prop.table(margin.col.f)
    } else {
        margin.col.f <- margin.table(tab,1)
        margin.col.p <- rep(1, times = length(tab))
    }

    margins<-list(row.freq = margin.row.f,
                  row.prop = margin.row.p,
                  col.freq = margin.col.f,
                  col.prop = margin.col.p)

    # This controls the display in the individual cells.
    if (format == "column_percent" | format == "col_percent"){
        tab<-round(prop.table(tab, 2)*100, 1)
    } else if (format == "row_percent"){
        tab<-round(prop.table(tab, 1)*100, 1)
    } else if (format == "total_percent"){
        tab<-round(100*tabf/sum(tab), 1)
    }

    # Change to a data frame matrix to make it more flexible
    if (length(dim(tab)) !=  1) {
        tab<-as.data.frame.matrix(tab)
    } else {
        tab <- as.data.frame(t(as.matrix(tab)))
        row.names(tab) <- "N"
    }
     for(i in c(1:ncol(tab))) {
        tab[,i] <- as.character(tab[,i])
    }

    tab <- add_marginals(tab, tabn, row.margin.format, col.margin.format, margins)

     crosstab<-list(
                   tab = tab,
                   n = tabn,
                   title = title,
                   margins = margins,
                   factors = factorsToUse,
                   formula = formula
                    )
    class(crosstab)<-c("crosstab")

    crosstab

}

#' Add marginals
#' Add requested marginals to the table

add_marginals <- function(tab, tabn,  row.margin.format, col.margin.format, margins){

    # Handle one row table. These are horizontal single variable tables. Handling is partially for educational purposes.
    if (dim(tab)[1] == 1){
        if (row.margin.format == "percent") {

                marginal.row <- as.vector(t(round(100*margins$row.prop, 1)))

                tab <- rbind(tab, marginal.row)
                row.names(tab)[2] <- "Row Percent"

        }
        if (col.margin.format == "percent") {
            # This should always be a row of 100s
            cm<-as.character(round(100*margins$col.prop, 1))
            tab <- rbind(tab, cm)

            row.names(tab)[nrow(tab)]<-"Column Percent"

        }
        return(tab)
    }

    if (row.margin.format != "none") {
        if (row.margin.format == 'percent'){

                tab$Total <- round(100*margins$row.prop, 1)

            names(tab)[names(tab)=="Total"] <- "Percent"
            #tab$Percent <- as.character(tab$Percent)

        } else {
            tab$Total <- margins$row.freq
            tab$Total <- as.character(tab$Total)
        }

    }

    # The column margins go horizontally along the bottom
    if (col.margin.format != "none") {

        if (col.margin.format == 'percent'){
            cm<-as.character(round(100*margins$col.prop, 1))
            rn<- "Row Percent"

        } else  {
            cm<-margins$col.freq
            rn<-"Total N"
        }
     if (row.margin.format != "none"){
            cm<-c(cm, tabn)
     }


            tab<-rbind(tab,cm)

        if (exists("rn")){
            rownames(tab)[nrow(tab)]<-rn
        }
    }

    tab
}

#' Preprocess multidimensional tables
#' This converts multidimensional tables to two dimensions

preprocess_multidimensional_tables <- function(tab, row.vars, col.vars, pretty.print, nvars ){

    # this is for 3+ variables, basically we make it be 2 variables
    tab<-as.data.frame(tab)

    cname <- paste(col.vars, collapse = " ")
    rname<-paste(row.vars, collapse = " ")

    # Merge the labels for the column variables into a single label with line breaks.
    if (length(col.vars) > 1  ) {
        septouse = ifelse(pretty.print, "\\\n", " ")
        tab$colvars <- with(tab, paste(tab[,length(row.vars)+1],tab[,nvars], sep = septouse))
        # Preserve the order
        tab_levels <- unique(tab$colvars)

    } else {
        tab$colvars <-with(tab,tab[,length(row.vars) +1])
    }

    # Merge the labels for row variables into a single label with a space.
    if (length(row.vars) > 1){
        tab$rowvars <- paste(tab[,1], tab[,length(row.vars)], sep = " ")
    } else {
        tab$rowvars <- with(tab, tab[,row.vars])
    }

    form <- as.formula(paste0("Freq ~ rowvars + colvars"))
    tab<-xtabs(Freq ~ rowvars + as.ordered(colvars), data = tab)
    names(dimnames(tab))<-list(rname, cname)
    tab <- tab[,tab_levels]

    tab
}
lehmansociology/lehmansociology documentation built on Jan. 9, 2018, 12:46 a.m.