funcionesMBO:

crosstab <- function (..., dec.places = NULL,
                      type = NULL,
                      style = "wide",
                      row.vars = NULL,
                      col.vars = NULL,
                      percentages = TRUE,
                      addmargins = TRUE,
                      subtotals=TRUE)
  # http://rstudio-pubs-static.s3.amazonaws.com/6975_c4943349b6174f448104a5513fed59a9.html
  ###################################################################################
  #                                                                                 #
  # Function created by Dr Paul Williamson, Dept. of Geography and Planning,        #
  # School of Environmental Sciences, University of Liverpool, UK.                  #
  #                                                                                 #
  # Adapted from the function ctab() in the catspec packge.                         #
  #                                                                                 #
  # Version: 12th July 2013                                                         #
  #                                                                                 #
  # Output best viewed using the companion function print.crosstab()                #
#                                                                                 #
###################################################################################


#Declare function used to convert frequency counts into relevant type of proportion or percentage
{
  mk.pcnt.tbl <- function(tbl, type) {
    a <- length(row.vars)
    b <- length(col.vars)
    mrgn <- switch(type, column.pct = c(row.vars[-a], col.vars),
                   row.pct = c(row.vars, col.vars[-b]),
                   joint.pct = c(row.vars[-a], col.vars[-b]),
                   total.pct = NULL)
    tbl <- prop.table(tbl, mrgn)
    if (percentages) {
      tbl <- tbl * 100
    }
    tbl
  }

  #Find no. of vars (all; row; col) for use in subsequent code
  n.row.vars <- length(row.vars)
  n.col.vars <- length(col.vars)
  n.vars <- n.row.vars + n.col.vars


  #Check to make sure all user-supplied arguments have valid values
  stopifnot(as.integer(dec.places) == dec.places, dec.places > -1)
  #type: see next section of code
  stopifnot(is.character(style))
  stopifnot(is.logical(percentages))
  stopifnot(is.logical(addmargins))
  stopifnot(is.logical(subtotals))
  stopifnot(n.vars>=1)

  #Convert supplied table type(s) into full text string (e.g. "f" becomes "frequency")
  #If invalid type supplied, failed match gives user automatic error message
  types <- NULL
  choices <- c("frequency", "row.pct", "column.pct", "joint.pct", "total.pct")
  for (tp in type) types <- c(types, match.arg(tp, choices))
  type <- types

  #If no type supplied, default to 'frequency + total' for univariate tables and to
  #'frequency' for multi-dimenstional tables

  #For univariate table....
  if (n.vars == 1) {
    if (is.null(type)) {
      # default = freq count + total.pct
      type <- c("frequency", "total.pct")
      #row.vars <- 1
    } else {
      #and any requests for row / col / joint.pct must be changed into requests for 'total.pct'
      type <- ifelse(type == "frequency", "frequency", "total.pct")
    }
    #For multivariate tables...
  } else if (is.null(type)) {
    # default = frequency count
    type <- "frequency"
  }



  #Check for integrity of requested analysis and adjust values of function arguments as required

  if ((addmargins==FALSE) & (subtotals==FALSE)) {
    warning("WARNING: Request to suppress subtotals (subtotals=FALSE) ignored because no margins requested (addmargins=FALSE)")
    subtotals <- TRUE
  }

  if ((n.vars>1) & (length(type)>1) & (addmargins==TRUE)) {
    warning("WARNING: Only row totals added when more than one table type requested")
    #Code lower down selecting type of margin implements this...
  }

  if ((length(type)>1) & (subtotals==FALSE)) {
    warning("WARNING: Can only request supply one table type if requesting suppression of subtotals; suppression of subtotals not executed")
    subtotals <- TRUE
  }

  if ((length(type)==1) & (subtotals==FALSE)) {
    choices <- c("frequency", "row.pct", "column.pct", "joint.pct", "total.pct")
    tp <- match.arg(type, choices)
    if (tp %in% c("row.pct","column.pct","joint.pct")) {
      warning("WARNING: subtotals can only be suppressed for tables of type 'frequency' or 'total.pct'")
      subtotals<- TRUE
    }
  }

  if ((n.vars > 2) & (n.col.vars>1) & (subtotals==FALSE))
    warning("WARNING: suppression of subtotals assumes only 1 col var; table flattened accordingly")


  if ( (subtotals==FALSE) & (n.vars>2) )  {
    #If subtotals not required AND total table vars > 2
    #Reassign all but last col.var as row vars
    #[because, for simplicity, crosstabs assumes removal of subtotals uses tables with only ONE col var]
    #N.B. Subtotals only present in tables with > 2 cross-classified vars...
    if (length(col.vars)>1) {
      row.vars <- c(row.vars,col.vars[-length(col.vars)])
      col.vars <- col.vars[length(col.vars)]
      n.row.vars <- length(row.vars)
      n.col.vars <- 1
    }
  }

  #If dec.places not set by user, set to 2 unlesss only one table of type frequency requested,
  #in which case set to 0.  [Leaves user with possibility of having frequency tables with > 0 dp]
  if (is.null(dec.places)) {
    if ((length(type)==1) & (type[1]=="frequency")) {
      dec.places <- 0
    } else {
      dec.places <-2
    }
  }

  #Take the original input data, whatever form originally supplied in,
  #convert into table format using requested row and col vars, and save as 'tbl'

  args <- list(...)

  if (length(args) > 1) {
    if (!all(sapply(args, is.factor)))
      stop("If more than one argument is passed then all must be factors")
    tbl <- table(...)
  }
  else {
    if (is.factor(...)) {
      tbl <- table(...)
    }
    else if (is.table(...)) {
      tbl <- eval(...)
    }
    else if (is.data.frame(...)) {
      #tbl <- table(...)
      if (is.null(row.vars) && is.null(col.vars)) {
        tbl <- table(...)
      }
      else {
        var.names <- c(row.vars,col.vars)
        A <- (...)
        tbl <- table(A[var.names])
        if(length(var.names==1)) names(dimnames(tbl)) <- var.names
        #[table() only autocompletes dimnames for multivariate crosstabs of dataframes]
      }
    }
    else if (class(...) == "ftable") {
      tbl <- eval(...)
      if (is.null(row.vars) && is.null(col.vars)) {
        row.vars <- names(attr(tbl, "row.vars"))
        col.vars <- names(attr(tbl, "col.vars"))
      }
      tbl <- as.table(tbl)
    }
    else if (class(...) == "ctab") {
      tbl <- eval(...)
      if (is.null(row.vars) && is.null(col.vars)) {
        row.vars <- tbl$row.vars
        col.vars <- tbl$col.vars
      }
      for (opt in c("dec.places", "type", "style", "percentages",
                    "addmargins", "subtotals")) if (is.null(get(opt)))
                      assign(opt, eval(parse(text = paste("tbl$", opt,
                                                          sep = ""))))
      tbl <- tbl$table
    }
    else {
      stop("first argument must be either factors or a table object")
    }
  }

  #Convert supplied table style into full text string (e.g. "l" becomes "long")
  style <- match.arg(style, c("long", "wide"))

  #Extract row and col names to be used in creating 'tbl' from supplied input data
  nms <- names(dimnames(tbl))
  z <- length(nms)
  if (!is.null(row.vars) && !is.numeric(row.vars)) {
    row.vars <- order(match(nms, row.vars), na.last = NA)
  }
  if (!is.null(col.vars) && !is.numeric(col.vars)) {
    col.vars <- order(match(nms, col.vars), na.last = NA)
  }
  if (!is.null(row.vars) && is.null(col.vars)) {
    col.vars <- (1:z)[-row.vars]
  }
  if (!is.null(col.vars) && is.null(row.vars)) {
    row.vars <- (1:z)[-col.vars]
  }
  if (is.null(row.vars) && is.null(col.vars)) {
    col.vars <- z
    row.vars <- (1:z)[-col.vars]
  }

  #Take the original input data, converted into table format using supplied row and col vars (tbl)
  #and create a second version (crosstab) which stores results as percentages if a percentage table type is requested.
  if (type[1] == "frequency")
    crosstab <- tbl
  else
    crosstab <- mk.pcnt.tbl(tbl, type[1])


  #If multiple table types requested, create and add these to
  if (length(type) > 1) {
    tbldat <- as.data.frame.table(crosstab)
    z <- length(names(tbldat)) + 1
    tbldat[z] <- 1
    pcntlab <- type
    pcntlab[match("frequency", type)] <- "Count"
    pcntlab[match("row.pct", type)] <- "Row %"
    pcntlab[match("column.pct", type)] <- "Column %"
    pcntlab[match("joint.pct", type)] <- "Joint %"
    pcntlab[match("total.pct", type)] <- "Total %"
    for (i in 2:length(type)) {
      if (type[i] == "frequency")
        crosstab <- tbl
      else crosstab <- mk.pcnt.tbl(tbl, type[i])
      crosstab <- as.data.frame.table(crosstab)
      crosstab[z] <- i
      tbldat <- rbind(tbldat, crosstab)
    }
    tbldat[[z]] <- as.factor(tbldat[[z]])
    levels(tbldat[[z]]) <- pcntlab
    crosstab <- xtabs(Freq ~ ., data = tbldat)
    names(dimnames(crosstab))[z - 1] <- ""
  }


  #Add margins if required, adding only those margins appropriate to user request
  if (addmargins==TRUE) {

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

    if (length(type)==1) {
      if (type=="row.pct")
      { crosstab <- addmargins(crosstab,margin=c(vars[n.vars]))
      tbl <- addmargins(tbl,margin=c(vars[n.vars]))
      }
      else
      { if (type=="column.pct")
      { crosstab <- addmargins(crosstab,margin=c(vars[n.row.vars]))
      tbl <- addmargins(tbl,margin=c(vars[n.row.vars]))
      }
        else
        { if (type=="joint.pct")
        { crosstab <- addmargins(crosstab,margin=c(vars[(n.row.vars)],vars[n.vars]))
        tbl <- addmargins(tbl,margin=c(vars[(n.row.vars)],vars[n.vars]))
        }
          else #must be total.pct OR frequency
          { crosstab <- addmargins(crosstab)
          tbl <- addmargins(tbl)
          }
        }
      }
    }

    #If more than one table type requested, only adding row totals makes any sense...
    if (length(type)>1) {
      crosstab <- addmargins(crosstab,margin=c(vars[n.vars]))
      tbl <- addmargins(tbl,margin=c(vars[n.vars]))
    }

  }


  #If subtotals not required, and total vars > 2, create dataframe version of table, with relevent
  #subtotal rows / cols dropped [Subtotals only present in tables with > 2 cross-classified vars]
  t1 <- NULL
  if ( (subtotals==FALSE) & (n.vars>2) )  {

    #Create version of crosstab in ftable format
    t1 <- crosstab
    t1 <- ftable(t1,row.vars=row.vars,col.vars=col.vars)

    #Convert to a dataframe
    t1 <- as.data.frame(format(t1),stringsAsFactors=FALSE)

    #Remove backslashes from category names AND colnames
    t1 <- apply(t1[,],2, function(x) gsub("\"","",x))
    #Remove preceding and trailing spaces from category names to enable accurate capture of 'sum' rows/cols
    #[Use of grep might extrac category labels with 'sum' as part of a longer one or two word string...]
    t1 <- apply(t1,2,function(x) gsub("[[:space:]]*$","",gsub("^[[:space:]]*","",x)))

    #Reshape dataframe to that variable and category labels display as required
    #(a) Move col category names down one row; and move col variable name one column to right
    t1[2,(n.row.vars+1):ncol(t1)] <- t1[1,(n.row.vars+1):ncol(t1)]
    t1[1,] <- ""
    t1[1,(n.row.vars+2)] <- t1[2,(n.row.vars+1)]
    #(b) Drop the now redundant column separating the row.var labels from the table data + col.var labels
    t1 <- t1[,-(n.row.vars+1)]

    #In 'lab', assign category labels for each variable to all rows (to allow identification of sub-totals)
    lab <- t1[,1:n.row.vars]
    for (c in 1:n.row.vars) {
      for (r in 2:nrow(lab)) {
        if (lab[r,c]=="") lab[r,c] <- lab[r-1,c]
      }
    }

    lab <- (apply(lab[,1:n.row.vars],2,function(x) x=="Sum"))
    lab <- apply(lab,1,sum)
    #Filter out rows of dataframe containing subtotals

    t1 <- t1[((lab==0) | (lab==n.row.vars)),]

    #Move the 'Sum' label associated with last row to the first column; in the process
    #setting the final row labels associated with other row variables to ""
    t1[nrow(t1),1] <- "Sum"
    t1[nrow(t1),(2:n.row.vars)] <- ""

    #set row and column names to NULL
    rownames(t1) <- NULL
    colnames(t1) <- NULL

  }



  #Create output object 'result' [class: crosstab]
  result <- NULL
  #(a) record of argument values used to produce tabular output
  result$row.vars <- row.vars
  result$col.vars <- col.vars
  result$dec.places <- dec.places
  result$type <- type
  result$style <- style
  result$percentages <- percentages
  result$addmargins <- addmargins
  result$subtotals <- subtotals

  #(b) tabular output [3 variants]
  result$table <- tbl  #Stores original cross-tab frequency counts without margins [class: table]
  result$crosstab <- crosstab #Stores cross-tab in table format using requested style(frequency/pct) and table margins (on/off)
  #[class: table]
  result$crosstab.nosub <- t1  #crosstab with subtotals suppressed [class: dataframe; or NULL if no subtotals suppressed]
  class(result) <- "crosstab"

  #Return 'result' as output of function
  result

}