data_summaries_r.qmd

---
title: "Data Summaries in R"
author: "Wade K. Copeland"
date: last-modified
date-format: "MMMM DD, YYYY"
output-file: index.html
bibliography: references.bib
format:
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appendix-style: plain
engine: jupyter
knitr:
    opts_knit:
        root.dir: "./"
---

<!-- To Do -->

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# Introduction

An essential part of any data analysis project is to understand the data at hand.  For this task, we will create a function that takes as input a variable from the data, a categorical variable to describe by, and returns summary tables and plots.

This tutorial uses the R programming language [@Rlang2019].  All of the files needed to reproduce these results can be downloaded from the Git repository <a href="https://github.com/wkingc/data-summaries-r/" target="_blank">https://github.com/wkingc/data-summaries-r</a>.

# Required Libraries

The libraries <i>knitr</i>, <i>bookdown</i>, and <i>kableExtra</i> are used to generate the HTML output [@knitr; @bookdown; @kableExtra].  The <i>ggplot2</i> library is loaded for the example data set that is used in this tutorial [@ggplot2].  The <i>Hmisc</i> library provides functionality needed to create variable labels [@Hmisc].  The libraries <i>reshape2</i> and <i>dplyr</i> are loaded for their data manipulation funtions [@dplyr; @reshape2].

```{r libraries, eval = TRUE, echo = TRUE, results = FALSE, warning = FALSE, message = FALSE}
library("knitr")
library("bookdown")
library("kableExtra")
library("ggplot2")
library("Hmisc")
library("reshape2")
library("dplyr")
```

# Example Data Setup

The data set used in this tutorial is <b>mpg</b> from the <i>ggplot2</i> package.  From the description in the manual:

> This dataset contains a subset of the fuel economy data that the EPA makes available <a href="http://fueleconomy.gov" target="_blank">here</a>. It contains only models which had a new release every year between 1999 and 2008 - this was used as a proxy for the popularity of the car.

```{r ExampleDataSetup, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
set.seed(123)
data(mpg)
mpg <- data.frame(mpg)

colnames(mpg)[which(colnames(mpg) == "manufacturer")] <- "manu"

mpg$manu <- factor(mpg$manu)
mpg$model <- factor(mpg$model)
mpg$displ <- as.numeric(mpg$displ)
mpg$year <- factor(mpg$year, levels = c("1999", "2008"), ordered = TRUE)

mpg$dp <- as.Date(NA, origin = "1970-01-01")
mpg$dp[which(mpg$year == "1999")] <- sample(seq(as.Date('1999-01-01', format = "%Y-%m-%d", origin = "1970-01-01"), as.Date('1999-12-25', format = "%Y-%m-%d", origin = "1970-01-01"), by="day"), dim(mpg)[1]/2)
mpg$dp[which(mpg$year == "2008")] <- sample(seq(as.Date('2008-01-01', format = "%Y-%m-%d", origin = "1970-01-01"), as.Date('2008-12-25', format = "%Y-%m-%d", origin = "1970-01-01"), by="day"), dim(mpg)[1]/2)
mpg$dp[sample(1:length(mpg$dp), size = 20)] <- NA
mpg$dp[10] <- as.Date('1000-05-02', format = "%Y-%m-%d", origin = "1970-01-01")

mpg$dplt <- as.POSIXlt(NA, origin = "1970-01-01 0:0:0")
mpg$dplt[which(mpg$year == "1999")] <- sample(seq(as.POSIXlt('1999-01-01 0:0:0', format = "%Y-%m-%d %H:%M:%S", origin = "1970-01-01 0:0:0"), as.POSIXlt('1999-12-25 0:0:0', format = "%Y-%m-%d %H:%M:%S", origin = "1970-01-01 0:0:0"), by="min"), dim(mpg)[1]/2)
mpg$dplt[which(mpg$year == "2008")] <- sample(seq(as.POSIXlt('2008-01-01 0:0:0', format = "%Y-%m-%d %H:%M:%S", origin = "1970-01-01 0:0:0"), as.POSIXlt('2008-12-25 0:0:0', format = "%Y-%m-%d %H:%M:%S", origin = "1970-01-01 0:0:0"), by="sec"), dim(mpg)[1]/2)
mpg$dplt[sample(1:length(mpg$dplt), size = 20)] <- NA

mpg$dpct <- as.POSIXct(NA, origin = "1970-01-01 0:0:0")
mpg$dpct[which(mpg$year == "1999")] <- sample(seq(as.POSIXct('1999-01-01 0:0:0', format = "%Y-%m-%d %H:%M:%S", origin = "1970-01-01 0:0:0"), as.POSIXct('1999-12-25 0:0:0', format = "%Y-%m-%d %H:%M:%S", origin = "1970-01-01 0:0:0"), by="min"), dim(mpg)[1]/2)
mpg$dpct[which(mpg$year == "2008")] <- sample(seq(as.POSIXct('2008-01-01 0:0:0', format = "%Y-%m-%d %H:%M:%S", origin = "1970-01-01 0:0:0"), as.POSIXct('2008-12-25 0:0:0', format = "%Y-%m-%d %H:%M:%S", origin = "1970-01-01 0:0:0"), by="sec"), dim(mpg)[1]/2)
mpg$dpct[sample(1:length(mpg$dpct), size = 20)] <- NA

mpg$cyl <- factor(mpg$cyl, levels = c(4, 5, 6, 8), ordered = TRUE)

mpg$trans <- factor(mpg$trans)
mpg$drv <- factor(mpg$drv, levels = c("f", "r", "4"), labels = c("front-wheel drive", "rear wheel drive", "4wd"))
mpg$fl <- factor(mpg$fl)
mpg$class <- factor(mpg$class)

mpg$rn <- rnorm(dim(mpg)[1], mean = 10, sd = 5)
mpg$rn[sample(1:length(mpg$rn), size = 50)] <- NA

mpg$rdifftime <- rnorm(dim(mpg)[1], mean = 10, sd = 5)
mpg$rdifftime[sample(1:length(mpg$rdifftime), size = 50)] <- NA
mpg$rdifftime <- as.difftime(mpg$rdifftime, units = "weeks")
mpg$rdifftime[which(mpg$rdifftime < 0)] <- 0

mpg$logical <- mpg$rdifftime >= 10

mpg$party <- factor(sample(c("republican", "democrat", "independent", NA), dim(mpg)[1], replace = TRUE), levels = c("republican", "democrat", "independent"))

mpg$comments <- sample(c("I like this car!", "Meh.", "This is the worst car ever!", "Does it come in green?", "want cheese flavoured cars.", "Does it also fly?", "Blah, Blah, Blah, Blah, Blah, Blah, Blah, Blah", "Missing", ".", NA), dim(mpg)[1], replace = TRUE)

mpg$miss <- NA

label(mpg$manu) <- "manufacturer"
label(mpg$model) <- "model name"
label(mpg$displ) <- "engine displacement, in litres"
label(mpg$year) <- "year of manufacture"
label(mpg$dp) <- "date of purchase (Date class)"
label(mpg$dplt) <- "date of purchase (POSIXlt class)"
label(mpg$dpct) <- "date of purchase (POSIXct class)"
label(mpg$cyl) <- "number of cylinders"
label(mpg$trans) <- "type of transmission"
label(mpg$drv) <- "drive type"
label(mpg$cty) <- "city miles per gallon"
label(mpg$hwy) <- "highway miles per gallon"
label(mpg$fl) <- "fuel type"
label(mpg$class) <- "type of car"
label(mpg$rn) <- "some random numbers that are generated from a normal distrubtion with mean = 10 and sd = 5"
label(mpg$rdifftime) <- "some random numbers that are generated from a normal distrubtion with mean = 10 and sd = 5, and then converted to weeks"
label(mpg$logical) <- "some random numbers that are generated from a normal distrubtion with mean = 10 and sd = 5, and then converted to weeks, and then set to TRUE if the difference is greater than 10"
label(mpg$party) <- "some random political parties"
label(mpg$comments) <- "some random comments"
label(mpg$miss) <- "an all missing variable"

kable(head(mpg), caption = "Header of <b>mpg</b>.", booktabs = TRUE, escape = FALSE) %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"))
```

# Data Summary Function

Below are a set of functions I wrote to using S4 (see <a href="https://www.cyclismo.org/tutorial/R/s4Classes.html" target="_blank">https://www.cyclismo.org/tutorial/R/s4Classes.html</a> for a gentle introduction to object oriented programming in R), culminating into a single function called <b>data_summary</b>.  The basic structure uses an object of class <i>dataSummaries</i> and then, based on the class of <b>x</b>, the <i>dataSummariesSetup</i> method applied to the <i>dataSummaries</i> class, returns an object of class <i>dataSummariesCharacter</i>, <i>dataSummariesNumeric</i>, <i>dataSummariesDate</i>, or <i>dataSummariesDifftime</i>.  Each of these four output classes inherits from the <i>dataSummaries</i> class; thus any method written for <i>dataSummaries</i> also applies to the four classes that inherit from it.

As input the <b>data_summary</b> function takes a variable to summarize (<b>x</b>), an optional variable or variables (as a character string) to summarize by (<b>by</b>), the data (<b>data</b>), and the units to use for <i>difftime</i> if <b>x</b> refers to a <i>Date</i>, <i>POSIXlt</i>, <i>POSIXct</i>, or <i>difftime</i> object in the <b>data</b>.

As output, the function returns an object of class <i>dataSummaries</i>.  The function has a <i>show</i> method and a method called <i>make_output</i> that generates <i>knitr</i> friendly output.  The summary table and plot can also be accessed individually through their accessor functions, <i>data_summary_table</i>, and <i>data_summary_plot</i>, respectively.

```{r dataSummaryFun, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
setOldClass(c("ggplot", "gg"))

dataSummaries <- setClass(
    "dataSummaries",
    
    slots = c(
        x = "character",
        by = "character",
        data = "data.frame",
        difftime_units = "character",
        xLab = "character",
        byLab = "character",
        table = "data.frame",
        plot = "ANY"
    ),
    
    prototype = list(
        x = character(0),
        by = character(0),
        data = data.frame(),
        difftime_units = character(0),
        xLab = character(0),
        byLab = character(0),
        table = data.frame(),
        plot = NULL
    ),
)

invisible(setValidity("dataSummaries", function(object) {
  if (!is.null(object@plot) && !inherits(object@plot, "ggplot")) {
    return("The 'plot' slot must be a ggplot object or NULL.")
  }
  TRUE
}))

dataSummariesCharacter <- setClass(
    "dataSummariesCharacter",
    
    slots = c(
        type = "character"
    ),
    
    prototype = list(
        type = character(0)
    ),
    
    contains = "dataSummaries"
)

dataSummariesNumeric <- setClass(
    "dataSummariesNumeric",
    
    slots = c(
        type = "character"
    ),
    
    prototype = list(
        type = character(0)
    ),
    
    contains = "dataSummaries"
)

dataSummariesDate <- setClass(
    "dataSummariesDate",
    
    slots = c(
        type = "character"
    ),
    
    prototype = list(
        type = character(0)
    ),
    
    contains = "dataSummaries"
)

dataSummariesDifftime <- setClass(
    "dataSummariesDifftime",
    
    slots = c(
        type = "character"
    ),
    
    prototype = list(
        type = character(0)
    ),
    
    contains = "dataSummaries"
)

invisible(setGeneric(name = "dataSummariesSetup", def = function(object) standardGeneric("dataSummariesSetup")))
setMethod(
    f = "dataSummariesSetup",
    signature = "dataSummaries", 
    definition = function(object) 
    {
        x = object@x
        by = object@by
        data = object@data
        
        xLab <- label(data[, x])
        colnames(data)[which(colnames(data) == x)] <- "var"
        
        if (length(by) == 0) {
            data$by <- factor(data$by <- "")
            label(data$by) <- ""
            byLab <- label(data$by)
        } else {
            data$by <- interaction(data[, by], sep = ", ")
            byLab <- paste(label(data[, by]), collapse = " by ")
            
            overall <- data
            overall$by <- "Overall"
            data <- rbind(data, overall)
        }
        
        data <- data[, c("var", "by")]
        
        if ("labelled" %in% class(data$var)) {
            class(data$var) <- class(data$var)[(-1)*which(class(data$var) == "labelled")]
        }
        
        object@xLab <- xLab
        object@byLab <- byLab
        object@data <- data
        
        if (any(c("character", "factor", "logical") %in% class(data$var))) { 
            return(dataSummariesCharacter(object, type = class(data$var)))
        } else if (any(c("numeric", "integer") %in% class(data$var))) {
            return(dataSummariesNumeric(object, type = class(data$var))) 
        } else if (any(c("Date", "POSIXlt", "POSIXct", "POSIXt") %in% class(data$var))) {
            if (length(object@difftime_units) == 0) stop("You need to specify the units for the difference in time.  See help(difftime) for additional information.")
            return(dataSummariesDate(object, type = class(data$var))) 
        } else if ("difftime" %in% class(data$var)) {
            if (length(object@difftime_units) == 0) stop("You need to specify the units for the difference in time.  See help(difftime) for additional information.")
            return(dataSummariesDifftime(object, type = class(data$var))) 
        } else {
            stop("x is an unsupported class")
        }
    }
)

invisible(setGeneric(name = "data_summary_switch", def = function(object) standardGeneric("data_summary_switch")))

setMethod(
    f = "data_summary_switch",
    signature = "dataSummariesCharacter", 
    definition = function(object) 
    {
        xLab <- object@xLab
        byLab <- object@byLab
        data <- object@data
        
        freqs <- table(data$var, data$by, useNA = "ifany", dnn = c(xLab, byLab))
        
        rownames(freqs)[which(is.na(rownames(freqs)))] <- "R NA Value"
        colnames(freqs)[which(is.na(colnames(freqs)))] <- "R NA Value" 
        
        props <- round(100*prop.table(freqs, 2), 2)
        
        res <- freqs
        for (i in 1:dim(freqs)[2]) {
            res[, i] <- paste(freqs[, i], " (", props[, i], "%)", sep = "")
        }
        res <- as.data.frame(res)
        colnames(res) <- c("var", "by", "freq")
        res <- dcast(res, var ~ by, value.var = "freq")
        colnames(res)[1] <- xLab
        if (byLab == "") colnames(res)[2] <- "n (%)"
        
        pData <- as.data.frame(props)
        colnames(pData) <- c("var", "by", "freq")
        
        levs <- as.character(pData$var)
        tmp <- nchar(levs)
        strCombRes <- list()
        for (k in 1:length(levs)) {
            strRes <- list()
            j = 0
            for (i in 1:ceiling(max(tmp)/30)) {
                strRes[[i]] <- substr(levs[k], j, 30*i)
                j = 30*i + 1
            }
            strCombRes[[k]] <- unlist(strRes)    
        }
        
        foo <- function(x) {
            if (!(length(which(x == "")) == 0)) x <- x[-1*which(x == "")]
            x <- paste(x, collapse = "\n")
            
            return(x)
        }
        
        levs <- unlist(lapply(strCombRes, foo))
        
        pData$names <- factor(rownames(pData), levels = rownames(pData), labels = levs)
        pData <- pData[, -1]
        
        colfunc <- colorRampPalette(c("#e41a1c","#377eb8","#4daf4a","#984ea3","#ff7f00"))
        colors <- colfunc(length(levels(pData$names)))
        
        p = ggplot(data = pData, aes(x = by, y = freq, fill = names)) +
            scale_fill_manual(values = colors) + 
            geom_bar(stat = "identity") + 
            xlab(paste(strwrap(xLab, width = 60), collapse = "\n")) +
            ylab("Percent") +
            theme(
                axis.line = element_line(colour = "black"),
                panel.border = element_rect(colour = "black", fill = NA, size = 1),
                axis.text = element_text(size = 12),
                axis.text.x = element_text(angle = 50, hjust = 1),
                axis.title = element_text(size = 12),
                legend.title = element_blank(),
                legend.position = "right",
                panel.grid = element_line(color = "lightgray"),
                panel.background = element_rect(fill = "white", colour = "white"))
        
        object@table <- res
        object@plot <- p
        
        return(object)
    }
)

setMethod(
    f = "data_summary_switch",
    signature = "dataSummariesNumeric", 
    definition = function(object) 
    {
        xLab <- object@xLab
        byLab <- object@byLab
        data <- object@data
        
        if (any(is.na(data$by))) {
            byLevs <- levels(data$by)
            data$by <- as.character(data$by)
            
            data$by[which(is.na(as.character(data$by)))] <- "R NA Value"
            data$by <- factor(data$by, levels = c(byLevs, "R NA Value"))
        }
        
        percMiss <- function(x) res <- round((length(which(is.na(x)))/length(x))*100, 2)
        
        res <- data %>%
            group_by(by) %>%
            summarize(
                label = xLab,
                n = length(na.omit(var)),
                miss = percMiss(var),
                mean = round(mean(var, na.rm = TRUE), 2),
                sd = round(sd(var, na.rm = TRUE), 2),
                median = round(median(var, na.rm = TRUE), 2),
                mad = round(mad(var, na.rm = TRUE), 2),
                q25 = round(quantile(var, probs = 0.25, na.rm = TRUE, type = 1), 2),
                q75 = round(quantile(var, probs = 0.75, na.rm = TRUE, type = 1), 2),
                IQR = round(IQR(var, na.rm = TRUE), 2),
                min = round(min(var, na.rm = TRUE), 2),
                max = round(max(var, na.rm = TRUE), 2)
            )
        
        res <- data.frame(res)
        
        colnames(res) <- c(byLab, "Label", "N", "P NA", "Mean", "S Dev", "Med", "MAD", "25th P", "75th P", "IQR", "Min", "Max")
        
        pData <- na.omit(data.frame(data[, c("var", "by")]))
        
        p = ggplot(data = pData, aes(x = by, y = var)) +
            geom_boxplot(position = position_dodge(1), fill = "#2c7bb6") +
            xlab(byLab) +
            ylab(paste(strwrap(xLab, width = 40), collapse = "\n")) +
            theme(
                axis.line = element_line(colour = "black"),
                panel.border = element_rect(colour = "black", fill = NA, size = 1),
                legend.position = "none",
                axis.text = element_text(size = 12),
                axis.text.x = element_text(angle = 50, hjust = 1),
                axis.title = element_text(size = 12), 
                panel.grid = element_line(color = "lightgray"),
                panel.background = element_rect(fill = "white", colour = "white"))
        
        object@table <- res
        object@plot <- p
        
        return(object)
    }
)

setMethod(
    f = "data_summary_switch",
    signature = "dataSummariesDate", 
    definition = function(object) 
    {
        xLab <- object@xLab
        byLab <- object@byLab
        data <- object@data
        difftime_units <- object@difftime_units
        
        if (any(is.na(data$by))) {
            byLevs <- levels(data$by)
            data$by <- as.character(data$by)
            
            data$by[which(is.na(as.character(data$by)))] <- "R NA Value"
            data$by <- factor(data$by, levels = c(byLevs, "R NA Value"))
        }
        
        percMiss <- function(x) round((length(which(is.na(x)))/length(x))*100, 2)
        
        sdDate <- function(x) {
            res <- difftime(x, mean(x, na.rm = TRUE), units = "secs")
            res <- as.numeric(as.character(res))
            res <- sd(res, na.rm = TRUE)
            res <- as.difftime(res, units = "secs")
            units(res) <- difftime_units
            
            return(res)
        }
        
        sdDate(data$var)
        
        madDate <- function(x) {
            res <- difftime(x, mean(x, na.rm = TRUE), units = "secs")
            res <- as.numeric(as.character(res))
            res <- mad(res, na.rm = TRUE)
            res <- as.difftime(res, units = "secs")
            units(res) <- difftime_units
            
            return(res)
        }
        
        dquantile <- function(x, probs){
            sx <- sort(x)
            pos <- round(probs*length(x))
            return(sx[pos])
        }
        
        q25Date <- function(x) dquantile(x, probs = 0.25)
        
        q75Date <- function(x) dquantile(x, probs = 0.75)
        
        IQRdate <- function(x) {
            res <- difftime(dquantile(x, probs = 0.75), dquantile(x, probs = 0.25), units = "secs")
            units(res) <- difftime_units
            return(res)
        }
        
        res <- data %>%
            group_by(by) %>%
            summarize(
                label = xLab,
                n = length(na.omit(var)),
                miss = percMiss(var),
                mean = mean(var, na.rm = TRUE),
                sd = round(sdDate(var), 2),
                median = median(var, na.rm = TRUE),
                mad = round(madDate(var), 2),
                q25 = q25Date(var),
                q75 = q75Date(var),
                IQR = IQRdate(var),
                min = min(var, na.rm = TRUE),
                max = max(var, na.rm = TRUE)
            )
        
        res <- data.frame(res)
        
        colnames(res) <- c(byLab, "Label", "N", "P NA", "Mean", "S Dev", "Med", "MAD", "25th P", "75th P", "IQR", "Min", "Max")
        
        pData <- na.omit(data.frame(data[, c("var", "by")]))
        
        if ("POSIXlt" %in% class(pData$var)) pData$var <- as.POSIXct(pData$var)
        
        p = ggplot(data = pData, aes(x = by, y = var)) +
            geom_boxplot(position = position_dodge(1), fill = "#2c7bb6") +
            xlab(byLab) +
            ylab(paste(strwrap(xLab, width = 40), collapse = "\n")) +
            theme(
                axis.line = element_line(colour = "black"),
                panel.border = element_rect(colour = "black", fill = NA, size = 1),
                legend.position = "none",
                axis.text = element_text(size = 12),
                axis.text.x = element_text(angle = 50, hjust = 1),
                axis.title = element_text(size = 12), 
                panel.grid = element_line(color = "lightgray"),
                panel.background = element_rect(fill = "white", colour = "white"))
        
        object@table <- res
        object@plot <- p
        
        return(object)
    }
)

setMethod(
    f = "data_summary_switch",
    signature = "dataSummariesDifftime", 
    definition = function(object) 
    {
        xLab <- object@xLab
        byLab <- object@byLab
        data <- object@data
        difftime_units <- object@difftime_units
        
        if (any(is.na(data$by))) {
            byLevs <- levels(data$by)
            data$by <- as.character(data$by)
            
            data$by[which(is.na(as.character(data$by)))] <- "R NA Value"
            data$by <- factor(data$by, levels = c(byLevs, "R NA Value"))
        }
        
        percMiss <- function(x) res <- round((length(which(is.na(x)))/length(x))*100, 2)
        
        units(data$var) <- "days"
        
        meanDate <- function(x) {
            res <- mean(x, na.rm = TRUE)
            units(res) <- difftime_units
            return(res)
        }
        
        medianDate <- function(x) {
            res <- median(x, na.rm = TRUE)
            units(res) <- difftime_units
            return(res)
        }
        
        sdDate <- function(x) {
            res <- as.difftime(sd(as.numeric(x), na.rm = TRUE), format = "%X", units = "days")
            units(res) <- difftime_units
            return(res)
        }
        
        madDate <- function(x) {
            res <- as.difftime(mad(as.numeric(x), na.rm = TRUE), format = "%X", units = "days")
            units(res) <- difftime_units
            return(res)
        }
        
        q25Date <- function(x) {
            res <- as.difftime(quantile(as.numeric(x), probs = 0.25, na.rm = TRUE, type = 1), units = "days")
            units(res) <- difftime_units
            return(res)
        }
        
        q75Date <- function(x) {
            res <- as.difftime(quantile(as.numeric(x), probs = 0.75, na.rm = TRUE, type = 1), units = "days")
            units(res) <- difftime_units
            return(res)
        }
        
        IQRdate <- function(x) {
            res <- as.difftime(IQR(as.numeric(x), na.rm = TRUE), format = "%X", units = "days")
            units(res) <- difftime_units
            return(res)
        }
        
        minDate <- function(x) {
            res <- as.difftime(min(as.numeric(x), na.rm = TRUE), format = "%X", units = "days")
            units(res) <- difftime_units
            return(res)
        }
        
        maxDate <- function(x) {
            res <- as.difftime(max(as.numeric(x), na.rm = TRUE), format = "%X", units = "days")
            units(res) <- difftime_units
            return(res)
        }  
        
        res <- data %>%
            group_by(by) %>%
            summarize(
                label = xLab,
                n = length(na.omit(var)),
                miss = percMiss(var),
                mean = round(meanDate(var), 2),
                sd = round(sdDate(var), 2),
                median = round(medianDate(var), 2),
                mad = round(madDate(var), 2),
                q25 = round(q25Date(var), 2),
                q75 = round(q75Date(var), 2),
                IQR = round(IQRdate(var), 2),
                min = round(minDate(var), 2),
                max = round(maxDate(var), 2)
            )
        
        res <- data.frame(res)
        
        colnames(res) <- c(byLab, "Label", "N", "P NA", "Mean", "S Dev", "Med", "MAD", "25th P", "75th P", "IQR", "Min", "Max")
        
        pData <- na.omit(data.frame(data[, c("var", "by")]))
        units(pData$var) <- difftime_units
        
        p = ggplot(data = pData, aes(x = by, y = var)) +
            geom_boxplot(position = position_dodge(1), fill = "#2c7bb6") +
            xlab(byLab) +
            ylab(paste(strwrap(xLab, width = 40), collapse = "\n")) +
            theme(
                axis.line = element_line(colour = "black"),
                panel.border = element_rect(colour = "black", fill = NA, size = 1),
                legend.position = "none",
                axis.text = element_text(size = 12),
                axis.text.x = element_text(angle = 50, hjust = 1),
                axis.title = element_text(size = 12), 
                panel.grid = element_line(color = "lightgray"),
                panel.background = element_rect(fill = "white", colour = "white"))
        
        object@table <- res
        object@plot <- p
        
        return(object)
    }
)

setMethod(
    f = "show",
    signature = "dataSummaries", 
    definition = function(object) 
    {
        print(object@table)
        print(object@plot)
    }
)

invisible(setGeneric(name = "make_kable_output", def = function(object) standardGeneric("make_kable_output")))
setMethod(
    f = "make_kable_output",
    signature = "dataSummaries", 
    definition = function(object) 
    {
        if (object@byLab == "") {
            print(
                kable(
                    object@table, caption = paste("Summary statistics of ", object@xLab, ".", sep = ""), booktabs = TRUE, table.attr = "data-quarto-disable-processing=true") %>% 
                    kable_styling(bootstrap_options = c("striped", "hover"), full_width = TRUE, font_size = 14))
        } else {
            print(
                kable(
                    object@table, caption = paste("Summary statistics of ", object@xLab, " by ", object@byLab, ".", sep = ""), booktabs = TRUE, table.attr = "data-quarto-disable-processing=true") %>% 
                    kable_styling(bootstrap_options = c("striped", "hover"), full_width = TRUE, font_size = 14))
        }
    }
)

invisible(setGeneric(name = "make_complete_output", def = function(object) standardGeneric("make_complete_output")))
setMethod(
    f = "make_complete_output",
    signature = "dataSummaries", 
    definition = function(object) 
    {
        if (object@byLab == "") {
            print(
                kable(
                    object@table, caption = paste("Summary statistics of ", object@xLab, ".", sep = ""), booktabs = TRUE, table.attr = "data-quarto-disable-processing=true") %>% 
                    kable_styling(bootstrap_options = c("striped", "hover"), full_width = TRUE, font_size = 14))
        } else {
            print(
                kable(
                    object@table, caption = paste("Summary statistics of ", object@xLab, " by ", object@byLab, ".", sep = ""), booktabs = TRUE, table.attr = "data-quarto-disable-processing=true") %>% 
                    kable_styling(bootstrap_options = c("striped", "hover"), full_width = TRUE, font_size = 14))
        }
        
        print(object@plot)
    }
)

invisible(setGeneric(name = "data_summary_table", def = function(object) standardGeneric("data_summary_table")))
setMethod(
    f = "data_summary_table",
    signature = "dataSummaries", 
    definition = function(object) 
    {
        object@table
    }
)

invisible(setGeneric(name = "data_summary_plot", def = function(object) standardGeneric("data_summary_plot")))
setMethod(
    f = "data_summary_plot",
    signature = "dataSummaries", 
    definition = function(object) 
    {
        object@plot
    }
)

data_summary <- function(x, by = character(0), data, difftime_units = character(0)) {
    object = dataSummaries(x = x, data = data, by = by, difftime_units = difftime_units)
    object = dataSummariesSetup(object)
    object = data_summary_switch(object)
}
```

# Examples
::: {.panel-tabset .tabset-fade .tabset-pills}

## Categorical
::: {.panel-tabset .tabset-fade .tabset-pills}

For a categorical variable <b>x</b>, we only need to specify <b>x</b> and the <b>data</b>.

```{r cylSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
cylSummaryExample <- data_summary(x = "cyl", data = mpg)
```

### Show method to output table and plot

```{r cylSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(cylSummaryExample)
```

### Output the summary table

```{r cylSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(cylSummaryExample)
```

### Output the plot

```{r cylSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(cylSummaryExample)
```

### Generate knitr friendly summary table

```{r cylSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
make_kable_output(cylSummaryExample)
```

### Generate knitr friendly output

```{r cylSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$cyl), ".", sep = "")}
make_complete_output(cylSummaryExample)
```

:::

## Categorical By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a categorical variable with by, we need to specify <b>x</b>, a <b>by</b> variable, and the <b>data</b>.

```{r cylByYearSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
cylByYearSummaryExample <- data_summary(x = "cyl", by = "year", data = mpg)
```

### Show method to output table and plot

```{r cylByYearSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(cylByYearSummaryExample)
```

### Output the summary table

```{r cylByYearSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(cylByYearSummaryExample)
```

### Output the plot

```{r cylByYearSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(cylByYearSummaryExample)
```

### Generate a knitr friendly summary table

```{r cylByYearSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(cylByYearSummaryExample)
```

### Generate knitr friendly output

```{r cylByYearSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$cyl), " by ", label(mpg$year), ".", sep = "")}
make_complete_output(cylByYearSummaryExample)
```

:::

## Categorical By By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a categorical variable with two or more by variables, we need to specify <b>x</b>, the <b>by</b> variables as a character string, and the <b>data</b>.

```{r cylByYearByPartySummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
cylByYearByPartySummaryExample <- data_summary(x = "cyl", by = c("year", "party"), data = mpg)
```

### Show method to output table and plot

```{r cylByYearByPartySummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(cylByYearByPartySummaryExample)
```

### Output the summary table

```{r cylByYearByPartySummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(cylByYearByPartySummaryExample)
```

### Output the plot

```{r cylByYearByPartySummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(cylByYearByPartySummaryExample)
```

### Generate a knitr friendly summary table

```{r cylByYearByPartySummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(cylByYearByPartySummaryExample)
```

### Generate knitr friendly output

```{r cylByYearByPartySummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$cyl), " by ", label(mpg$year), " by ", label(mpg$party), ".", sep = "")}
make_complete_output(cylByYearByPartySummaryExample)
```

:::

## Continuous
::: {.panel-tabset .tabset-fade .tabset-pills}

For a continuous variable <b>x</b>, we only need to specify <b>x</b> and the <b>data</b>.

```{r ctySummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
ctySummaryExample <- data_summary(x = "cty", data = mpg)
```

### Show method to output table and plot

```{r ctySummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(ctySummaryExample)
```

### Output the summary table

```{r ctySummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(ctySummaryExample)
```

### Output the plot

```{r ctySummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(ctySummaryExample)
```

### Generate knitr friendly summary table

```{r ctySummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
make_kable_output(ctySummaryExample)
```

### Generate knitr friendly output

```{r ctySummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$cty), ".", sep = "")}
make_complete_output(ctySummaryExample)
```

:::

## Continuous By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a continuous variable with by, we need to specify <b>x</b>, a <b>by</b> variable, and the <b>data</b>.

```{r ctyByCylSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
ctyByCylSummaryExample <- data_summary(x = "cty", by = "cyl", data = mpg)
```

### Show method to output table and plot

```{r ctyByCylSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(ctyByCylSummaryExample)
```

### Output the summary table

```{r ctyByCylSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(ctyByCylSummaryExample)
```

### Output the plot

```{r ctyByCylSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(ctyByCylSummaryExample)
```

### Generate a knitr friendly summary table

```{r ctyByCylSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(ctyByCylSummaryExample)
```

### Generate knitr friendly output

```{r ctyByCylSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$cty), " by ", label(mpg$cyl), ".", sep = "")}
make_complete_output(ctyByCylSummaryExample)
```

:::

## Continuous By By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a continuous variable with two or more by variables, we need to specify <b>x</b>, the <b>by</b> variables as a character string, and the <b>data</b>.

```{r ctyByCylByYearSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
ctyByCylByYearSummaryExample <- data_summary(x = "cty", by = c("cyl", "year"), data = mpg)
```

### Show method to output table and plot

```{r ctyByCylByYearSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(ctyByCylByYearSummaryExample)
```

### Output the summary table

```{r ctyByCylByYearSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(ctyByCylByYearSummaryExample)
```

### Output the plot

```{r ctyByCylByYearSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(ctyByCylByYearSummaryExample)
```

### Generate a knitr friendly summary table

```{r ctyByCylByYearSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(ctyByCylByYearSummaryExample)
```

### Generate knitr friendly output

```{r ctyByCylByYearSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$cty), " by ", label(mpg$cyl), " by ", label(mpg$year), ".", sep = "")}
make_complete_output(ctyByCylByYearSummaryExample)
```

:::

## Date
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable <b>x</b>, we need to specify <b>x</b>, the <b>data</b>, and <b>difftime_units</b>.

```{r dpSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
dpSummaryExample <- data_summary(x = "dp", data = mpg[which(mpg$dp != "1000-05-02" | is.na(mpg$dp)), ], difftime_units = "weeks")
```

### Show method to output table and plot

```{r dpSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(dpSummaryExample)
```

### Output the summary table

```{r dpSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(dpSummaryExample)
```

### Output the plot

```{r dpSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(dpSummaryExample)
```

### Generate knitr friendly summary table

```{r dpSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
make_kable_output(dpSummaryExample)
```

### Generate knitr friendly output

```{r dpSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$dp), ".", sep = "")}
make_complete_output(dpSummaryExample)
```

:::

## Date By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable with by, we need to specify <b>x</b>, a <b>by</b> variable, the <b>data</b>, and <b>difftime_units</b>.

```{r dpByCylSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
dpByCylSummaryExample <- data_summary(x = "dp", by = "cyl", data = mpg[which(mpg$dp != "1000-05-02" | is.na(mpg$dp)), ], difftime_units = "weeks")
```

### Show method to output table and plot

```{r dpByCylSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(dpByCylSummaryExample)
```

### Output the summary table

```{r dpByCylSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(dpByCylSummaryExample)
```

### Output the plot

```{r dpByCylSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(dpByCylSummaryExample)
```

### Generate a knitr friendly summary table

```{r dpByCylSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(dpByCylSummaryExample)
```

### Generate knitr friendly output

```{r dpByCylSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$dp), " by ", label(mpg$cyl), ".", sep = "")}
make_complete_output(dpByCylSummaryExample)
```

:::

## Date By By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable with two or more by variables, we need to specify <b>x</b>, the <b>by</b> variables as a character string, the <b>data</b>, and <b>difftime_units</b>.

```{r dpByCylByCommentsSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
dpByCylByCommentsSummaryExample <- data_summary(x = "dp", by = c("cyl", "comments"), data = mpg[which(mpg$dp != "1000-05-02" | is.na(mpg$dp)), ], difftime_units = "weeks")
```

### Show method to output table and plot

```{r dpByCylByCommentsSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(dpByCylByCommentsSummaryExample)
```

### Output the summary table

```{r dpByCylByCommentsSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(dpByCylByCommentsSummaryExample)
```

### Output the plot

```{r dpByCylByCommentsSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 8, fig.asp = 0.8}
data_summary_plot(dpByCylByCommentsSummaryExample)
```

### Generate a knitr friendly summary table

```{r dpByCylByCommentsSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(dpByCylByCommentsSummaryExample)
```

### Generate knitr friendly output

```{r dpByCylByCommentsSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 8, fig.asp = 0.8, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$dp), " by ", label(mpg$cyl), " by ", label(mpg$comments), ".", sep = "")}
make_complete_output(dpByCylByCommentsSummaryExample)
```

:::

## POSIXlt Date
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable <b>x</b>, we need to specify <b>x</b>, the <b>data</b>, and <b>difftime_units</b>.

```{r dpltSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
dpltSummaryExample <- data_summary(x = "dplt", data = mpg, difftime_units = "weeks")
```

### Show method to output table and plot

```{r dpltSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(dpltSummaryExample)
```

### Output the summary table

```{r dpltSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(dpltSummaryExample)
```

### Output the plot

```{r dpltSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(dpltSummaryExample)
```

### Generate knitr friendly summary table

```{r dpltSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
make_kable_output(dpltSummaryExample)
```

### Generate knitr friendly output

```{r dpltSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$dp), ".", sep = "")}
make_complete_output(dpltSummaryExample)
```

:::

## POSIXlt Date By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable with by, we need to specify <b>x</b>, a <b>by</b> variable, the <b>data</b>, and <b>difftime_units</b>.

```{r dpltByCylSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
dpltByCylSummaryExample <- data_summary(x = "dplt", by = "cyl", data = mpg, difftime_units = "weeks")
```

### Show method to output table and plot

```{r dpltByCylSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(dpltByCylSummaryExample)
```

### Output the summary table

```{r dpltByCylSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(dpltByCylSummaryExample)
```

### Output the plot

```{r dpltByCylSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(dpltByCylSummaryExample)
```

### Generate a knitr friendly summary table

```{r dpltByCylSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(dpltByCylSummaryExample)
```

### Generate knitr friendly output

```{r dpltByCylSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$dp), " by ", label(mpg$cyl), ".", sep = "")}
make_complete_output(dpltByCylSummaryExample)
```

:::

## POSIXlt Date By By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable with two or more by variables, we need to specify <b>x</b>, the <b>by</b> variables as a character string, the <b>data</b>, and <b>difftime_units</b>.

```{r dpltByCylByCommentsSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
dpltByCylByCommentsSummaryExample <- data_summary(x = "dplt", by = c("cyl", "comments"), data = mpg, difftime_units = "weeks")
```

### Show method to output table and plot

```{r dpltByCylByCommentsSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(dpltByCylByCommentsSummaryExample)
```

### Output the summary table

```{r dpltByCylByCommentsSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(dpltByCylByCommentsSummaryExample)
```

### Output the plot

```{r dpltByCylByCommentsSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 8, fig.asp = 0.8}
data_summary_plot(dpltByCylByCommentsSummaryExample)
```

### Generate a knitr friendly summary table

```{r dpltByCylByCommentsSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(dpltByCylByCommentsSummaryExample)
```

### Generate knitr friendly output

```{r dpltByCylByCommentsSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 8, fig.asp = 0.8, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$dp), " by ", label(mpg$cyl), " by ", label(mpg$comments), ".", sep = "")}
make_complete_output(dpltByCylByCommentsSummaryExample)
```

:::

## POSIXct Date
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable <b>x</b>, we need to specify <b>x</b>, the <b>data</b>, and <b>difftime_units</b>.

```{r dpctSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
dpctSummaryExample <- data_summary(x = "dpct", data = mpg, difftime_units = "weeks")
```

### Show method to output table and plot

```{r dpctSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(dpctSummaryExample)
```

### Output the summary table

```{r dpctSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(dpctSummaryExample)
```

### Output the plot

```{r dpctSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(dpctSummaryExample)
```

### Generate knitr friendly summary table

```{r dpctSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
make_kable_output(dpctSummaryExample)
```

### Generate knitr friendly output

```{r dpctSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$dp), ".", sep = "")}
make_complete_output(dpctSummaryExample)
```

:::

## POSIXct Date By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable with by, we need to specify <b>x</b>, a <b>by</b> variable, the <b>data</b>, and <b>difftime_units</b>.

```{r dpctByCylSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
dpctByCylSummaryExample <- data_summary(x = "dpct", by = "cyl", data = mpg, difftime_units = "weeks")
```

### Show method to output table and plot

```{r dpctByCylSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(dpctByCylSummaryExample)
```

### Output the summary table

```{r dpctByCylSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(dpctByCylSummaryExample)
```

### Output the plot

```{r dpctByCylSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(dpctByCylSummaryExample)
```

### Generate a knitr friendly summary table

```{r dpctByCylSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(dpctByCylSummaryExample)
```

### Generate knitr friendly output

```{r dpctByCylSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$dp), " by ", label(mpg$cyl), ".", sep = "")}
make_complete_output(dpctByCylSummaryExample)
```

:::

## POSIXct Date By By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable with two or more by variables, we need to specify <b>x</b>, the <b>by</b> variables as a character string, the <b>data</b>, and <b>difftime_units</b>.

```{r dpctByCylByCommentsSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
dpctByCylByCommentsSummaryExample <- data_summary(x = "dpct", by = c("cyl", "comments"), data = mpg, difftime_units = "weeks")
```

### Show method to output table and plot

```{r dpctByCylByCommentsSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(dpctByCylByCommentsSummaryExample)
```

### Output the summary table

```{r dpctByCylByCommentsSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(dpctByCylByCommentsSummaryExample)
```

### Output the plot

```{r dpctByCylByCommentsSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 8, fig.asp = 0.8}
data_summary_plot(dpctByCylByCommentsSummaryExample)
```

### Generate a knitr friendly summary table

```{r dpctByCylByCommentsSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(dpctByCylByCommentsSummaryExample)
```

### Generate knitr friendly output

```{r dpctByCylByCommentsSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 8, fig.asp = 0.8, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$dp), " by ", label(mpg$cyl), " by ", label(mpg$comments), ".", sep = "")}
make_complete_output(dpctByCylByCommentsSummaryExample)
```

:::

## Difftime
::: {.panel-tabset .tabset-fade .tabset-pills}

For a difftime variable <b>x</b>, we  need to specify <b>x</b>, the <b>data</b>, and <b>difftime_units</b>.

```{r rdifftimeSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
rdifftimeSummaryExample <- data_summary(x = "rdifftime", data = mpg, difftime_units = "weeks")
```

### Show method to output table and plot

```{r rdifftimeSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(rdifftimeSummaryExample)
```

### Output the summary table

```{r rdifftimeSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(rdifftimeSummaryExample)
```

### Output the plot

```{r rdifftimeSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(rdifftimeSummaryExample)
```

### Generate knitr friendly summary table

```{r rdifftimeSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
make_kable_output(rdifftimeSummaryExample)
```

### Generate knitr friendly output

```{r rdifftimeSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$rdifftime), ".", sep = "")}
make_complete_output(rdifftimeSummaryExample)
```

:::

## Difftime By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable with by, we need to specify <b>x</b>, a <b>by</b> variable, the <b>data</b>, and <b>difftime_units</b>.

```{r rdifftimeByDrvSummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
rdifftimeByDrvSummaryExample <- data_summary(x = "rdifftime", by = "drv", data = mpg, difftime_units = "weeks")
```

### Show method to output table and plot

```{r rdifftimeByDrvSummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(rdifftimeByDrvSummaryExample)
```

### Output the summary table

```{r rdifftimeByDrvSummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(rdifftimeByDrvSummaryExample)
```

### Output the plot

```{r rdifftimeByDrvSummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7}
data_summary_plot(rdifftimeByDrvSummaryExample)
```

### Generate a knitr friendly summary table

```{r rdifftimeByDrvSummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(rdifftimeByDrvSummaryExample)
```

### Generate knitr friendly output

```{r rdifftimeByDrvSummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$rdifftime), " by ", label(mpg$drv), ".", sep = "")}
make_complete_output(rdifftimeByDrvSummaryExample)
```

:::

## Difftime By By
::: {.panel-tabset .tabset-fade .tabset-pills}

For a date variable with two or more by variables, we need to specify <b>x</b>, the <b>by</b> variables as a character string, the <b>data</b>, and <b>difftime_units</b>.

```{r rdifftimeByDrvBypartySummaryExample, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
rdifftimeByDrvBypartySummaryExample <- data_summary(x = "rdifftime", by = c("drv", "party"), data = mpg, difftime_units = "weeks")
```

### Show method to output table and plot

```{r rdifftimeByDrvBypartySummaryExampleShow, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
show(rdifftimeByDrvBypartySummaryExample)
```

### Output the summary table

```{r rdifftimeByDrvBypartySummaryExampleTable, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
data_summary_table(rdifftimeByDrvBypartySummaryExample)
```

### Output the plot

```{r rdifftimeByDrvBypartySummaryExamplePlot, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, fig.width = 8, fig.asp = 0.8}
data_summary_plot(rdifftimeByDrvBypartySummaryExample)
```

### Generate a knitr friendly summary table

```{r rdifftimeByDrvBypartySummaryExampleKnitrTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
make_kable_output(rdifftimeByDrvBypartySummaryExample)
```

### Generate knitr friendly output

```{r rdifftimeByDrvBypartySummaryExampleComplete, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 8, fig.asp = 0.8, fig.align = 'center', fig.cap = paste("Stacked barplot of ", label(mpg$rdifftime), " by ", label(mpg$drv), " by ", label(mpg$party), ".", sep = "")}
make_complete_output(rdifftimeByDrvBypartySummaryExample)
```

:::
:::

# Data Summaries
::: {.panel-tabset .tabset-fade .tabset-pills}

## Manufacturer

```{r manuSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$manu), "</b>.", sep = "")}
manuSummary <- data_summary(x = "manu", data = mpg)

make_complete_output(manuSummary)
```

## Model Name

```{r modelSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$model), "</b>.", sep = "")}
modelSummary <- data_summary(x = "model", data = mpg)

make_complete_output(modelSummary)
```

## Engine Displacement (Litres)

```{r displSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$displ), "</b>.", sep = "")}
displSummary <- data_summary(x = "displ", data = mpg)

make_complete_output(displSummary)
```

## Year of Manufacture

```{r yearSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$year), "</b>.", sep = "")}
yearSummary <- data_summary(x = "year", data = mpg)

make_complete_output(yearSummary)
```

## Date of Purchase

```{r dpSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$dp), "</b>.", sep = "")}
dpSummary <- data_summary(x = "dp", data = mpg[which(mpg$dp != "1000-05-02" | is.na(mpg$dp)), ], difftime_units = "weeks")

make_complete_output(dpSummary)
```

## Number of Cylinders

```{r cylSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$cyl), "</b>.", sep = "")}
cylSummary <- data_summary(x = "cyl", data = mpg)

make_complete_output(cylSummary)
```

## Type of Transmission

```{r transSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>",  label(mpg$trans), "</b>.", sep = "")}
transSummary <- data_summary(x = "trans", data = mpg)

make_complete_output(transSummary)
```

## Drive Type

```{r drvSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>",  label(mpg$drv), "</b>.", sep = "")}
drvSummary <- data_summary(x = "drv", data = mpg)

make_complete_output(drvSummary)
```

## City MPG

```{r ctySummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>",  label(mpg$cty), "</b>.", sep = "")}
ctySummary <- data_summary(x = "cty", data = mpg)

make_complete_output(ctySummary)
```

## Highway MPG

```{r hwySummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>",  label(mpg$hwy), "</b>.", sep = "")}
hwySummary <- data_summary(x = "hwy", data = mpg)

make_complete_output(hwySummary)
```

## Fuel Type

```{r flSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>",  label(mpg$fl), "</b>.", sep = "")}
flSummary <- data_summary(x = "fl", data = mpg)

make_complete_output(flSummary)
```

## Type of Car

```{r classSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>",  label(mpg$class), "</b>.", sep = "")}
classSummary <- data_summary(x = "class", data = mpg)

make_complete_output(classSummary)
```

## Random Numbers

```{r rnSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>",  label(mpg$rn), "</b>.", sep = "")}
rnSummary <- data_summary(x = "rn", data = mpg)

make_complete_output(rnSummary)
```

## Random Difference in Time

```{r rdifftimeSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>",  label(mpg$rdifftime), "</b>.", sep = "")}
rdifftimeSummary <- data_summary(x = "rdifftime", difftime_units = "weeks", data = mpg)

make_complete_output(rdifftimeSummary)
```

## Random Difference in Time Greater than 10

```{r logicalSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>",  label(mpg$logical), "</b>.", sep = "")}
logicalSummary <- data_summary(x = "logical", difftime_units = "weeks", data = mpg)

make_complete_output(logicalSummary)
```

## Party

```{r partySummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>",  label(mpg$party), "</b>.", sep = "")}
partySummary <- data_summary(x = "party", data = mpg)

make_complete_output(partySummary)
```

## Comments

```{r commentsSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$comments), "</b>.", sep = "")}
commentsSummary <- data_summary(x = "comments", data = mpg)

make_complete_output(commentsSummary)
```

## All Missing

```{r missSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$miss), "</b>.", sep = "")}
missSummary <- data_summary(x = "miss", data = mpg)

make_complete_output(missSummary)
```

:::

# By Data Summaries

## By Drive Type
::: {.panel-tabset .tabset-fade .tabset-pills}

### Number of Cylinders by Drive Type

```{r cylByDrvSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$cyl), "</b> by <b>", label(mpg$drv), "</b>.", sep = "")}
cylByDrvSummary <- data_summary(x = "cyl", by = "drv", data = mpg)

make_complete_output(cylByDrvSummary)
```

### Date of Purchase by Drive Type

```{r dpByDrvSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$dp), "</b> by <b>", label(mpg$drv), "</b>.", sep = "")}
dpByDrvSummary <- data_summary(x = "dp", by = "drv", data = mpg[which(mpg$dp != "1000-05-02" | is.na(mpg$dp)), ], difftime_units = "weeks")

make_complete_output(dpByDrvSummary)
```

### Random Numbers by Drive Type

```{r rnByDrvSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$rn), "</b> by <b>", label(mpg$drv), "</b>.", sep = "")}
rnByDrvSummary <- data_summary(x = "rn", by = "drv", data = mpg)

make_complete_output(rnByDrvSummary)
```

### Random Difference in Time by Drive Type

```{r rdifftimeByDrvSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$rdifftime), "</b> by <b>", label(mpg$drv), "</b>.", sep = "")}
rdifftimeByDrvSummary <- data_summary(x = "rdifftime", by = "drv", difftime_units = "weeks", data = mpg)

make_complete_output(rdifftimeByDrvSummary)
```

### Random Difference in Time Greater than 10 by Drive Type

```{r logicalByDrvSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$logical), "</b> by <b>", label(mpg$drv), "</b>.", sep = "")}
logicalByDrvSummary <- data_summary(x = "logical", by = "drv", difftime_units = "weeks", data = mpg)

make_complete_output(logicalByDrvSummary)
```

### Comments by Drive Type

```{r commentsByDrvSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$comments), "</b> by <b>", label(mpg$drv), "</b>.", sep = "")}
commentsByDrvSummary <- data_summary(x = "comments", by = "drv", data = mpg)

make_complete_output(commentsByDrvSummary)
```

### All Missing by Drive Type

```{r missByDrvSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$miss), "</b> by <b>", label(mpg$drv), "</b>.", sep = "")}
missByDrvSummary <- data_summary(x = "miss", by = "drv", data = mpg)

make_complete_output(missByDrvSummary)
```

:::

## City and Highway MPG
::: {.panel-tabset .tabset-fade .tabset-pills}

### City MPG by Manufacturer

```{r ctyBymanuSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$manu), "</b>.", sep = "")}
ctyBymanuSummary <- data_summary(x = "cty", by = "manu", data = mpg)

make_complete_output(ctyBymanuSummary)
```

### Highway MPG by Manufacturer

```{r hwyBymanuSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$manu), "</b>.", sep = "")}
hwyBymanuSummary <- data_summary(x = "hwy", by = "manu", data = mpg)

make_complete_output(hwyBymanuSummary)
```

### City MPG by Model Name

```{r ctyBymodelSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$model), "</b>.", sep = "")}
ctyBymodelSummary <- data_summary(x = "cty", by = "model", data = mpg)

make_complete_output(ctyBymodelSummary)
```

### Highway MPG by Model Name

```{r hwyBymodelSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$model), "</b>.", sep = "")}
hwyBymodelSummary <- data_summary(x = "hwy", by = "model", data = mpg)

make_complete_output(hwyBymodelSummary)
```

### City MPG by Year of Manufacture

```{r ctyByYearSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$year), "</b>.", sep = "")}
ctyByYearSummary <- data_summary(x = "cty", by = "year", data = mpg)

make_complete_output(ctyByYearSummary)
```

### Highway MPG by Year of Manufacture

```{r hwyByYearSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$year), "</b>.", sep = "")}
hwyByYearSummary <- data_summary(x = "hwy", by = "year", data = mpg)

make_complete_output(hwyByYearSummary)
```

### City MPG by Number of Cylinders

```{r ctyByCylSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$cyl), "</b>.", sep = "")}
ctyByCylSummary <- data_summary(x = "cty", by = "cyl", data = mpg)

make_complete_output(ctyByCylSummary)
```

### Highway MPG by Number of Cylinders

```{r hwyByCylSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$cyl), "</b>.", sep = "")}
hwyByCylSummary <- data_summary(x = "hwy", by = "cyl", data = mpg)

make_complete_output(hwyByCylSummary)
```

### City MPG by Type of Transmission

```{r ctyBytransSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$trans), "</b>.", sep = "")}
ctyBytransSummary <- data_summary(x = "cty", by = "trans", data = mpg)

make_complete_output(ctyBytransSummary)
```

### Highway MPG by Type of Transmission

```{r hwyBytransSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$trans), "</b>.", sep = "")}
hwyBytransSummary <- data_summary(x = "hwy", by = "trans", data = mpg)

make_complete_output(hwyBytransSummary)
```

### City MPG by Drive Type

```{r ctyByDrvSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$drv), "</b>.", sep = "")}
ctyByDrvSummary <- data_summary(x = "cty", by = "drv", data = mpg)

make_complete_output(ctyByDrvSummary)
```

### Highway MPG by Drive Type

```{r hwyByDrvSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$drv), "</b>.", sep = "")}
hwyByDrvSummary <- data_summary(x = "hwy", by = "drv", data = mpg)

make_complete_output(hwyByDrvSummary)
```

### City MPG by Fuel Type

```{r ctyByflSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$fl), "</b>.", sep = "")}
ctyByflSummary <- data_summary(x = "cty", by = "fl", data = mpg)

make_complete_output(ctyByflSummary)
```

### Highway MPG by Fuel Type

```{r hwyByflSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$fl), "</b>.", sep = "")}
hwyByflSummary <- data_summary(x = "hwy", by = "fl", data = mpg)

make_complete_output(hwyByflSummary)
```

### City MPG by Type of Car

```{r ctyByclassSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$class), "</b>.", sep = "")}
ctyByclassSummary <- data_summary(x = "cty", by = "class", data = mpg)

make_complete_output(ctyByclassSummary)
```

### Highway MPG by Type of Car

```{r hwyByclassSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$class), "</b>.", sep = "")}
hwyByclassSummary <- data_summary(x = "hwy", by = "class", data = mpg)

make_complete_output(hwyByclassSummary)
```

### City MPG by Comments

```{r ctyByCommentsSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$comments), "</b>.", sep = "")}
ctyByCommentsSummary <- data_summary(x = "cty", by = "comments", data = mpg)

make_complete_output(ctyByCommentsSummary)
```

### Highway MPG by Comments

```{r hwyByCommentsSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$comments), "</b>.", sep = "")}
hwyByCommentsSummary <- data_summary(x = "hwy", by = "comments", data = mpg)

make_complete_output(hwyByCommentsSummary)
```

### City MPG by Party

```{r ctyByPartySummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$Party), "</b>.", sep = "")}
ctyByPartySummary <- data_summary(x = "cty", by = "party", data = mpg)

make_complete_output(ctyByPartySummary)
```

### Highway MPG by Party

```{r hwyByPartySummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$Party), "</b>.", sep = "")}
hwyByPartySummary <- data_summary(x = "hwy", by = "party", data = mpg)

make_complete_output(hwyByPartySummary)
```

### City MPG by All Missing

```{r ctyByMissSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$miss), "</b>.", sep = "")}
ctyByMissSummary <- data_summary(x = "cty", by = "miss", data = mpg)

make_complete_output(ctyByMissSummary)
```

### Highway MPG by All Missing

```{r hwyByMissSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$miss), "</b>.", sep = "")}
hwyByMissSummary <- data_summary(x = "hwy", by = "miss", data = mpg)

make_complete_output(hwyByMissSummary)
```

:::

## Other Examples
::: {.panel-tabset .tabset-fade .tabset-pills}

### Date of Purchase by Year of Manufacture

```{r dpByYearSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$dp), "</b> by <b>", label(mpg$year), "</b>.", sep = "")}
dpByYearSummary <- data_summary(x = "dp", by = "year", data = mpg[which(mpg$dp != "1000-05-02" | is.na(mpg$dp)), ], difftime_units = "weeks")

make_complete_output(dpByYearSummary)
```

### Date of Purchase by Comments

```{r dpByCommentsSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$dp), "</b> by <b>", label(mpg$comments), "</b>.", sep = "")}
dpByCommentsSummary <- data_summary(x = "dp", by = "comments", data = mpg[which(mpg$dp != "1000-05-02" | is.na(mpg$dp)), ], difftime_units = "weeks")

make_complete_output(dpByCommentsSummary)
```

### Random Number by Party

```{r rnByPartySummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$rn), "</b> by <b>", label(mpg$party), "</b>.", sep = "")}
rnByPartySummary <- data_summary(x = "rn", by = "party", data = mpg)

make_complete_output(rnByPartySummary)
```

### Random Difference in Time by Party

```{r rdifftimeByPartySummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$rdifftime), "</b> by <b>", label(mpg$party), "</b>.", sep = "")}
rdifftimeByPartySummary <- data_summary(x = "rdifftime", by = "party", difftime_units = "weeks", data = mpg)

make_complete_output(rdifftimeByPartySummary)
```

### Random Difference in Time by Comments

```{r rdifftimeByCommentsSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$rdifftime), "</b> by <b>", label(mpg$comments), "</b>.", sep = "")}
rdifftimeByCommentsSummary <- data_summary(x = "rdifftime", by = "comments", difftime_units = "weeks", data = mpg)

make_complete_output(rdifftimeByCommentsSummary)
```

### Comments by Party

```{r commentsByPartySummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Barplot of <b>", label(mpg$comments), "</b> by <b>", label(mpg$party), "</b>.", sep = "")}
commentsByPartySummary <- data_summary(x = "comments", by = "party", data = mpg)

make_complete_output(commentsByPartySummary)
```

:::

# By By Data Summaries
::: {.panel-tabset .tabset-fade .tabset-pills}

## City MPG by Number of Cylinders by Class

```{r ctyByCylByClassSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$cty), "</b> by <b>", label(mpg$cyl), "</b> by <b>", label(mpg$class), "</b>.", sep = "")}
ctyByCylByClassSummary <- data_summary(x = "cty", by = c("cyl", "class"), data = mpg)

make_complete_output(ctyByCylByClassSummary)
```

## Highway MPG by Number of Cylinders by Class

```{r hwyByCylByClassSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$hwy), "</b> by <b>", label(mpg$cyl), "</b> by <b>", label(mpg$class), "</b>.", sep = "")}
hwyByCylByClassSummary <- data_summary(x = "hwy", by = c("cyl", "class"), data = mpg)

make_complete_output(hwyByCylByClassSummary)
```

## Date of Purchase of Cylinders by Comments

```{r dpByCylByCommentsSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Boxplot of <b>", label(mpg$dp), "</b> by <b>", label(mpg$cyl), "</b> by <b>", label(mpg$class), "</b>.", sep = "")}
dpByCylByCommentsSummary <- data_summary(x = "dp", by = c("cyl", "comments"), difftime_units = "weeks", data = mpg[which(mpg$dp != "1000-05-02" | is.na(mpg$dp)), ])

make_complete_output(dpByCylByCommentsSummary)
```

## Comments by Number of Cylinders by Class

```{r commentsByCylByClassSummary, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE, fig.width = 7, fig.asp = 0.7, fig.align = 'center', fig.cap = paste("Stacked barplot of <b>", label(mpg$comments), "</b> by <b>", label(mpg$cyl), "</b> by <b>", label(mpg$class), "</b>.", sep = "")}
commentsByCylByClassSummary <- data_summary(x = "comments", by = c("cyl", "class"), data = mpg)

make_complete_output(commentsByCylByClassSummary)
```

:::

# Summary Tables
::: {.panel-tabset .tabset-fade .tabset-pills}

The full summaries with plots are useful for understanding the data and diagnosing issues, but eventually, you will want to summarise the data in a more digestible form.

## Univariate Data Summaries

```{r UnivariateDataSummaryTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
invisible(setGeneric(name = "univariate_data_summary", def = function(object) standardGeneric("univariate_data_summary")))
setMethod(
    f = "univariate_data_summary",
    signature = "dataSummaries", 
    definition = function(object) 
    {
        if (all(c("Mean", "S Dev") %in% colnames(object@table))) {
            xlab <- paste("<b>", object@xLab, ", Mean (SD)</b>", sep = "")
            
            if (length(object@difftime_units) > 0) {
                res <- paste(object@table[, "Mean"], " (", object@table[, "S Dev"], " ", object@difftime_units, ")", sep = "")
            } else {
                res <- paste(object@table[, "Mean"], " (", object@table[, "S Dev"], ")", sep = "")
            }
            
            res <- data.frame(res)
            res$rname <- xlab
            res <- res[, c(2, 1)]
            colnames(res) <- c("", "")
            rownames(res) <- NULL
        } else {
            xlab <- paste("<b>", object@xLab, ", n (%)", "</b>", sep = "")
            res <- c("", object@table[, -1])
            res <- data.frame(res, stringsAsFactors = FALSE)
            res$rnames <- c(xlab, paste("&nbsp;&nbsp;", as.character(object@table[, 1]), sep = ""))
            res <- res[, c(2, 1)]
            colnames(res) <- c("", "")
            rownames(res) <- NULL
        }
        
        return(res)
    }
)

univariateDataSummaryList <- list(
    manuSummary, 
    modelSummary, 
    displSummary, 
    yearSummary, 
    dpSummary, 
    cylSummary, 
    transSummary, 
    drvSummary, 
    ctySummary, 
    hwySummary, 
    flSummary, 
    classSummary, 
    rnSummary, 
    rdifftimeSummary,
    logicalSummary,
    partySummary, 
    commentsSummary,
    missSummary
)

cars_univariate_data_summary <- do.call("rbind", lapply(univariateDataSummaryList, univariate_data_summary))

kable(cars_univariate_data_summary, caption = "Data summaries", booktabs = TRUE, escape = FALSE, format = "html", table.attr = "data-quarto-disable-processing=true") %>% 
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = TRUE, font_size = 14)
```

## By Data Summaries

```{r ByDataSummaryTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
invisible(setGeneric(name = "by_data_summary", def = function(object) standardGeneric("by_data_summary")))
setMethod(
    f = "by_data_summary",
    signature = "dataSummaries", 
    definition = function(object) 
    {
        if (all(c("Mean", "S Dev") %in% colnames(object@table))) {
            res <- t(object@table[, c("Mean", "S Dev")])
            
            if (length(object@difftime_units) > 0) {
                res <- paste(object@table[, "Mean"], " (", object@table[, "S Dev"], " ", object@difftime_units, ")", sep = "")
            } else {
                res <- paste(object@table[, "Mean"], " (", object@table[, "S Dev"], ")", sep = "")
            }
            
            res <- data.frame(t(res))
            res$label <- paste("<b>", object@xLab, ", Mean (SD)</b>", sep = "")
            rownames(res) <- NULL
            res <- res[, c(which(colnames(res) == "label"), which(!(1:dim(res)[2] %in% which(colnames(res) == "label"))))]
            colnames(res) <- c("", as.character(object@table[, 1]))
        } else {
            res <- object@table
            res[, 1] <- paste("&nbsp;&nbsp;", res[, 1], sep = "")
            res <- rbind("", res)
            res[1,1] <- paste("<b>", object@xLab, ", N (%)</b>", sep = "")
            colnames(res)[1] <- ""
        }
        
        return(res)
    }
)

byDataSummaryList <- list(
    ctyByDrvSummary,
    hwyByDrvSummary,
    cylByDrvSummary,
    dpByDrvSummary,
    rnByDrvSummary,
    rdifftimeByDrvSummary,
    logicalByDrvSummary,
    commentsByDrvSummary,
    missByDrvSummary
)

cars_by_data_summary <- do.call("rbind", lapply(byDataSummaryList, by_data_summary))

kable(cars_by_data_summary, caption = "Data summaries", booktabs = TRUE, escape = FALSE, format = "html", table.attr = "data-quarto-disable-processing=true") %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = TRUE, font_size = 14)
```

## Bivariate Data Summaries

```{r BivariateDataSummaryTable, eval = TRUE, echo = TRUE, results = 'asis', warning = FALSE, message = FALSE}
invisible(setGeneric(name = "bivariate_data_summary", def = function(object1, object2) standardGeneric("bivariate_data_summary")))
setMethod(
    f = "bivariate_data_summary",
    signature = "dataSummaries", 
    definition = function(object1, object2) 
    {
        rnames <- c(paste("<b>", object1@byLab, "</b>", sep = ""), paste("&nbsp;&nbsp;", object1@table[, 1], sep = ""))
        
        if (length(object1@difftime_units) > 0) {
            object1Res <- data.frame(c("", paste(object1@table[, "Mean"], " (", object1@table[, "S Dev"], " ", object1@difftime_units, ")", sep = "")), stringsAsFactors = FALSE)
        } else {
            object1Res <- data.frame(c("", paste(object1@table[, "Mean"], " (", object1@table[, "S Dev"], ")", sep = "")), stringsAsFactors = FALSE)
        }       
        
        if (length(object2@difftime_units) > 0) {
            object2Res <- data.frame(c("", paste(object2@table[, "Mean"], " (", object1@table[, "S Dev"], " ", object2@difftime_units, ")", sep = "")), stringsAsFactors = FALSE)
        } else {
            object2Res <- data.frame(c("", paste(object2@table[, "Mean"], " (", object2@table[, "S Dev"], ")", sep = "")), stringsAsFactors = FALSE)
        }           
        
        res <- cbind(object1Res, object2Res)
        res <- cbind(rnames, res)
        
        colnames(res) <- c("", paste(object1@xLab, ", Mean (SD)", sep = ""), paste(object2@xLab, ", Mean (SD)", sep = ""))
        
        return(res)
    }
)

cars_bivariate_data_summary <- rbind(
    bivariate_data_summary(ctyBymanuSummary, hwyBymanuSummary),
    bivariate_data_summary(ctyBymodelSummary, hwyBymodelSummary),
    bivariate_data_summary(ctyByYearSummary, hwyByYearSummary),
    bivariate_data_summary(ctyByCylSummary, hwyByCylSummary),
    bivariate_data_summary(ctyBytransSummary, hwyBytransSummary),
    bivariate_data_summary(ctyByDrvSummary, hwyByDrvSummary),
    bivariate_data_summary(ctyByflSummary, hwyByflSummary),
    bivariate_data_summary(ctyByclassSummary, hwyByclassSummary),
    bivariate_data_summary(ctyByPartySummary, hwyByPartySummary),
    bivariate_data_summary(ctyByCommentsSummary, hwyByCommentsSummary),
    bivariate_data_summary(ctyByMissSummary, hwyByMissSummary)
)

kable(cars_bivariate_data_summary, caption = "By data summaries of miles per gallons for city and highway.", booktabs = TRUE, escape = FALSE, format = "html", table.attr = "data-quarto-disable-processing=true") %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = TRUE, font_size = 14)

cars_bivariate_time_data_summary <- rbind(
    bivariate_data_summary(ctyByPartySummary, rdifftimeByPartySummary),
    bivariate_data_summary(ctyByCommentsSummary, rdifftimeByCommentsSummary)
)

kable(cars_bivariate_time_data_summary, caption = "By data summaries of miles per gallons for city and random difference in time.", booktabs = TRUE, escape = FALSE, format = "html", table.attr = "data-quarto-disable-processing=true") %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = TRUE, font_size = 14)
```

:::

# R Session Information

```{r sessionInfo, eval = TRUE, echo = TRUE, results = TRUE, warning = FALSE, message = FALSE}
sessionInfo()
```

# References