include IQR and MAD in freq

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(as.data.frame,frequency_tbl)
 S3method(as.double,mic)
 S3method(as.integer,mic)
 S3method(as.numeric,mic)
@@ -53,6 +54,7 @@ export(rsi_df)
 export(rsi_predict)
 export(semi_join_microorganisms)
 export(top_freq)
+exportMethods(as.data.frame.frequency_tbl)
 exportMethods(as.double.mic)
 exportMethods(as.integer.mic)
 exportMethods(as.numeric.mic)
@@ -115,8 +117,8 @@ importFrom(rvest,html_node)
 importFrom(rvest,html_nodes)
 importFrom(rvest,html_table)
 importFrom(stats,fivenum)
+importFrom(stats,mad)
 importFrom(stats,pchisq)
-importFrom(stats,quantile)
 importFrom(stats,sd)
 importFrom(tibble,tibble)
 importFrom(utils,browseVignettes)

NEWS.md

@@ -2,6 +2,7 @@
 #### New
 * Function `top_freq` function to get the top/below *n* items of frequency tables
 * Vignette about frequency tables
+* Header of frequency tables now also show MAD and IQR
 * Possibility to globally set the default for the amount of items to print in frequency tables (`freq` function), with `options(max.print.freq = n)`
 * Functions `clipboard_import` and `clipboard_export` as helper functions to quickly copy and paste from/to software like Excel and SPSS
 * Function `g.test` to perform the Χ<sup>2</sup> distributed [*G*-test](https://en.wikipedia.org/wiki/G-test)

R/freq.R

@@ -19,40 +19,43 @@
 #' Frequency table
 #'
 #' Create a frequency table of a vector with items or a data frame. Supports quasiquotation and markdown for reports. \code{top_freq} can be used to get the top/bottom \emph{n} items of a frequency table, with counts as names.
-#' @param x vector with items, or \code{data.frame}
+#' @param x vector with items, or a \code{data.frame}
 #' @param ... up to nine different columns of \code{x} to calculate frequencies from, see Examples
-#' @param sort.count sort on count, i.e. frequencies. Use \code{FALSE} to sort alphabetically on item.
+#' @param sort.count sort on count, i.e. frequencies. This will be \code{TRUE} at default for everything except for factors.
-#' @param nmax number of row to print. The default, \code{15}, uses \code{\link{getOption}("max.print.freq")}. Use \code{nmax = 0}, \code{nmax = NULL} or \code{nmax = NA} to print all rows.
+#' @param nmax number of row to print. The default, \code{15}, uses \code{\link{getOption}("max.print.freq")}. Use \code{nmax = 0}, \code{nmax = Inf}, \code{nmax = NULL} or \code{nmax = NA} to print all rows.
-#' @param na.rm a logical value indicating whether NA values should be removed from the frequency table. The header will always print the amount of \code{NA}s.
+#' @param na.rm a logical value indicating whether \code{NA} values should be removed from the frequency table. The header will always print the amount of \code{NA}s.
 #' @param row.names a logical value indicating whether row indices should be printed as \code{1:nrow(x)}
 #' @param markdown print table in markdown format (this forces \code{nmax = NA})
 #' @param digits how many significant digits are to be used for numeric values in the header (not for the items themselves, that depends on \code{\link{getOption}("digits")})
 #' @param sep a character string to separate the terms when selecting multiple columns
 #' @param f a frequency table
 #' @param n number of top \emph{n} items to return, use -n for the bottom \emph{n} items. It will include more than \code{n} rows if there are ties.
-#' @details This package also has a vignette available about this function, run: \code{browseVignettes("AMR")} to read it.
+#' @details Frequency tables (or frequency distributions) are summaries of the distribution of values in a sample. With the `freq` function, you can create univariate frequency tables. Multiple variables will be pasted into one variable, so it forces a univariate distribution. This package also has a vignette available to explain the use of this function further, run \code{browseVignettes("AMR")} to read it.
 #'
-#' For numeric values of any class, these additional values will be calculated and shown into the header:
+#' For numeric values of any class, these additional values will all be calculated with \code{na.rm = TRUE} and shown into the header:
 #' \itemize{
 #'   \item{Mean, using \code{\link[base]{mean}}}
-#'   \item{Standard deviation, using \code{\link[stats]{sd}}}
+#'   \item{Standard Deviation, using \code{\link[stats]{sd}}}
-#'   \item{Five numbers of Tukey (min, Q1, median, Q3, max), using \code{\link[stats]{fivenum}}}
+#'   \item{Coefficient of Variation (CV), the standard deviation divided by the mean}
-#'   \item{Outliers (total count and unique count), using \code{\link{boxplot.stats}}}
+#'   \item{Mean Absolute Deviation (MAD), using \code{\link[stats]{mad}}}
-#'   \item{Coefficient of variation (CV), the standard deviation divided by the mean}
+#'   \item{Tukey Five-Number Summaries (minimum, Q1, median, Q3, maximum), using \code{\link[stats]{fivenum}}}
-#'   \item{Coefficient of quartile variation (CQV, sometimes called coefficient of dispersion), calculated as \code{(Q3 - Q1) / (Q3 + Q1)} using \code{\link{quantile}} with \code{type = 6} as quantile algorithm to comply with SPSS standards}
+#'   \item{Interquartile Range (IQR) calculated as \code{Q3 - Q1} using the Tukey Five-Number Summaries, i.e. \strong{not} using the \code{\link[stats]{quantile}} function}
+#'   \item{Coefficient of Quartile Variation (CQV, sometimes called coefficient of dispersion), calculated as \code{(Q3 - Q1) / (Q3 + Q1)} using the Tukey Five-Number Summaries}
+#'   \item{Outliers (total count and unique count), using \code{\link[grDevices]{boxplot.stats}}}
 #' }
 #'
-#' For dates and times of any class, these additional values will be calculated and shown into the header:
+#' For dates and times of any class, these additional values will be calculated with \code{na.rm = TRUE} and shown into the header:
 #' \itemize{
 #'   \item{Oldest, using \code{\link[base]{min}}}
 #'   \item{Newest, using \code{\link[base]{max}}, with difference between newest and oldest}
 #'   \item{Median, using \code{\link[stats]{median}}, with percentage since oldest}
 #' }
 #'
+#'
 #' The function \code{top_freq} uses \code{\link[dplyr]{top_n}} internally and will include more than \code{n} rows if there are ties.
-#' @importFrom stats fivenum sd quantile
+#' @importFrom stats fivenum sd mad
 #' @importFrom grDevices boxplot.stats
-#' @importFrom dplyr %>% select pull n_distinct group_by arrange desc mutate summarise
+#' @importFrom dplyr %>% select pull n_distinct group_by arrange desc mutate summarise n_distinct
 #' @importFrom utils browseVignettes
 #' @importFrom tibble tibble
 #' @keywords summary summarise frequency freq
@@ -88,17 +91,24 @@
 #'   filter(hospital_id == "A") %>%
 #'   freq(genus, species)
 #'
-#' # save frequency table to an object
-#' years <- septic_patients %>%
-#'   mutate(year = format(date, "%Y")) %>%
-#'   freq(year)
-#' years %>% pull(item)
-#'
 #' # get top 10 bugs of hospital A as a vector
 #' septic_patients %>%
 #'   filter(hospital_id == "A") %>%
 #'   freq(bactid) %>%
 #'   top_freq(10)
+#'
+#' # save frequency table to an object
+#' years <- septic_patients %>%
+#'   mutate(year = format(date, "%Y")) %>%
+#'   freq(year)
+#'
+#' # print only top 5
+#' years %>% print(nmax = 5)
+#'
+#' # transform to plain data.frame
+#' septic_patients %>%
+#'   freq(age) %>%
+#'   as.data.frame()
 frequency_tbl <- function(x,
                           ...,
                           sort.count = TRUE,
@@ -135,11 +145,6 @@ frequency_tbl <- function(x,
 
   mult.columns <- 0
 
-  if (NROW(x) == 0) {
-    cat('\nNo observations.\n')
-    return(invisible())
-  }
-
   if (!is.null(ncol(x))) {
     if (ncol(x) == 1 & any(class(x) == 'data.frame')) {
       x <- x %>% pull(1)
@@ -226,8 +231,8 @@ frequency_tbl <- function(x,
     x <- x[!x %in% NAs]
   }
 
-  if (missing(sort.count) & any(class(x) %in% c('double', 'integer', 'numeric', 'raw', 'single', 'factor'))) {
+  if (missing(sort.count) & 'factor' %in% class(x)) {
-    # sort on item/level at default when x is numeric or a factor and sort.count is not set
+    # sort on factor level at default when x is a factor and sort.count is not set
     sort.count <- FALSE
   }
 
@@ -246,28 +251,30 @@ frequency_tbl <- function(x,
   }
 
   if (is.list(x) | is.matrix(x) | is.environment(x) | is.function(x)) {
-    cat(header, "\n")
+    stop('frequency tables do not support lists, matrices, environments and functions.', call. = FALSE)
-    stop('`freq()` does not support lists, matrices, environments or functions.', call. = FALSE)
   }
 
   header <- header %>% paste0(markdown_line, '\nLength:    ', (NAs %>% length() + x %>% length()) %>% format(),
                               ' (of which NA: ', NAs %>% length() %>% format(),
-                              ' = ', (NAs %>% length() / (NAs %>% length() + x %>% length())) %>% percent(force_zero = TRUE), ')')
+                              ' = ', (NAs %>% length() / (NAs %>% length() + x %>% length())) %>% percent(force_zero = TRUE) %>% sub('NaN', '0', ., fixed = TRUE), ')')
   header <- header %>% paste0(markdown_line, '\nUnique:    ', x %>% n_distinct() %>% format())
 
-  if (any(class(x) %in% c('double', 'integer', 'numeric', 'raw', 'single'))) {
+  if (NROW(x) > 0 & any(class(x) %in% c('double', 'integer', 'numeric', 'raw', 'single'))) {
     # right align number
+    Tukey_five <- stats::fivenum(x, na.rm = TRUE)
     x_align <- 'r'
     header <- header %>% paste0('\n')
     header <- header %>% paste(markdown_line, '\nMean:     ', x %>% base::mean(na.rm = TRUE) %>% format(digits = digits))
     header <- header %>% paste0(markdown_line, '\nStd. dev.: ', x %>% stats::sd(na.rm = TRUE) %>% format(digits = digits),
-                                ' (CV: ', x %>% cv(na.rm = TRUE) %>% format(digits = digits), ')')
+                                ' (CV: ', x %>% cv(na.rm = TRUE) %>% format(digits = digits),
-    header <- header %>% paste0(markdown_line, '\nFive-Num:  ', x %>% stats::fivenum(na.rm = TRUE) %>% format(digits = digits) %>% trimws() %>% paste(collapse = '  |  '),
+                                ', MAD: ', x %>% stats::mad(na.rm = TRUE) %>% format(digits = digits), ')')
-                                ' (CQV: ', x %>% cqv(na.rm = TRUE) %>% format(digits = digits), ')')
+    header <- header %>% paste0(markdown_line, '\nFive-Num:  ', Tukey_five %>% format(digits = digits) %>% trimws() %>% paste(collapse = ' | '),
+                                ' (IQR: ', (Tukey_five[4] - Tukey_five[2]) %>% format(digits = digits),
+                                ', CQV: ', x %>% cqv(na.rm = TRUE) %>% format(digits = digits), ')')
     outlier_length <- length(boxplot.stats(x)$out)
     header <- header %>% paste0(markdown_line, '\nOutliers:  ', outlier_length)
     if (outlier_length > 0) {
-      header <- header %>% paste0(' (unique: ', boxplot.stats(x)$out %>% unique() %>% length(), ')')
+      header <- header %>% paste0(' (unique: ', boxplot.stats(x)$out %>% n_distinct(), ')')
     }
   }
 
@@ -276,7 +283,7 @@ frequency_tbl <- function(x,
     x <- x %>% as.POSIXlt()
     formatdates <- "%H:%M:%S"
   }
-  if (any(class(x) %in% c('Date', 'POSIXct', 'POSIXlt'))) {
+  if (NROW(x) > 0 & any(class(x) %in% c('Date', 'POSIXct', 'POSIXlt'))) {
     header <- header %>% paste0('\n')
     mindate <- x %>% min(na.rm = TRUE)
     maxdate <- x %>% max(na.rm = TRUE)
@@ -302,10 +309,9 @@ frequency_tbl <- function(x,
     nmax <- length(x)
   }
 
-  if (nmax == 0 | is.na(nmax) | is.null(nmax)) {
+  if (nmax %in% c(0, Inf, NA, NULL)) {
     nmax <- length(x)
   }
-  nmax.1 <- min(length(x), nmax + 1)
 
   # create table with counts and percentages
   column_names <- c('Item', 'Count', 'Percent', 'Cum. Count', 'Cum. Percent', '(Factor Level)')
@@ -404,12 +410,12 @@ top_freq <- function(f, n) {
   vect
 }
 
-#' @rdname print
+#' @rdname freq
 #' @exportMethod print.frequency_tbl
 #' @importFrom knitr kable
 #' @importFrom dplyr n_distinct
 #' @export
-print.frequency_tbl <- function(x, ...) {
+print.frequency_tbl <- function(x, nmax = getOption("max.print.freq", default = 15), ...) {
 
   opt <- attr(x, 'opt')
 
@@ -423,7 +429,12 @@ print.frequency_tbl <- function(x, ...) {
     title <- ""
   }
 
-  cat("Frequency table", title, "\n\n")
+  if (!missing(nmax)) {
+    opt$nmax <- nmax
+    opt$nmax.set <- TRUE
+  }
+
+  cat("Frequency table", title, "\n")
 
   if (!is.null(opt$header)) {
     cat(opt$header)
@@ -448,7 +459,13 @@ print.frequency_tbl <- function(x, ...) {
     x.unprinted <- base::sum(x[(opt$nmax + 1):nrow(x), 'count'], na.rm = TRUE)
     x.printed <- base::sum(x$count) - x.unprinted
 
-    x <- x[1:opt$nmax,]
+    if (opt$nmax.set == TRUE) {
+      nmax <- opt$nmax
+    } else {
+      nmax <- getOption("max.print.freq", default = 15)
+    }
+
+    x <- x[1:nmax,]
 
     if (opt$nmax.set == TRUE) {
       footer <- paste('[ reached `nmax = ', opt$nmax, '`', sep = '')
@@ -496,3 +513,12 @@ print.frequency_tbl <- function(x, ...) {
 
 }
 
+#' @noRd
+#' @exportMethod as.data.frame.frequency_tbl
+#' @export
+as.data.frame.frequency_tbl <- function(x, ...) {
+  attr(x, 'package') <- NULL
+  attr(x, 'package.version') <- NULL
+  attr(x, 'opt') <- NULL
+  as.data.frame.data.frame(x, ...)
+}

R/misc.R

@@ -91,10 +91,8 @@ cv <- function(x, na.rm = TRUE) {
 # Coefficient of dispersion, or coefficient of quartile variation (CQV).
 # (Bonett et al., 2006: Confidence interval for a coefficient of quartile variation).
 cqv <- function(x, na.rm = TRUE) {
-  cqv.x <-
+  fives <- stats::fivenum(x, na.rm = na.rm)
-    (stats::quantile(x, 0.75, na.rm = na.rm, type = 6) - stats::quantile(x, 0.25, na.rm = na.rm, type = 6)) /
+  (fives[4] - fives[2]) / (fives[4] + fives[2])
-    (stats::quantile(x, 0.75, na.rm = na.rm, type = 6) + stats::quantile(x, 0.25, na.rm = na.rm, type = 6))
-  unname(cqv.x)
 }
 
 # show bytes as kB/MB/GB

R/print.R

@@ -124,8 +124,6 @@ prettyprint_df <- function(x,
 
   if ('tbl_df' %in% class(x)) {
     type <- 'tibble'
-  } else if ('frequency_tbl' %in% class(x)) {
-    type <- 'frequency table'
   } else if ('data.table' %in% class(x)) {
     type <- 'data.table'
   } else {

man/freq.Rd

@@ -4,6 +4,7 @@
 \alias{freq}
 \alias{frequency_tbl}
 \alias{top_freq}
+\alias{print.frequency_tbl}
 \title{Frequency table}
 \usage{
 frequency_tbl(x, ..., sort.count = TRUE, nmax = getOption("max.print.freq"),
@@ -15,17 +16,20 @@ freq(x, ..., sort.count = TRUE, nmax = getOption("max.print.freq"),
   sep = " ")
 
 top_freq(f, n)
+
+\method{print}{frequency_tbl}(x, nmax = getOption("max.print.freq", default =
+  15), ...)
 }
 \arguments{
-\item{x}{vector with items, or \code{data.frame}}
+\item{x}{vector with items, or a \code{data.frame}}
 
 \item{...}{up to nine different columns of \code{x} to calculate frequencies from, see Examples}
 
-\item{sort.count}{sort on count, i.e. frequencies. Use \code{FALSE} to sort alphabetically on item.}
+\item{sort.count}{sort on count, i.e. frequencies. This will be \code{TRUE} at default for everything except for factors.}
 
-\item{nmax}{number of row to print. The default, \code{15}, uses \code{\link{getOption}("max.print.freq")}. Use \code{nmax = 0}, \code{nmax = NULL} or \code{nmax = NA} to print all rows.}
+\item{nmax}{number of row to print. The default, \code{15}, uses \code{\link{getOption}("max.print.freq")}. Use \code{nmax = 0}, \code{nmax = Inf}, \code{nmax = NULL} or \code{nmax = NA} to print all rows.}
 
-\item{na.rm}{a logical value indicating whether NA values should be removed from the frequency table. The header will always print the amount of \code{NA}s.}
+\item{na.rm}{a logical value indicating whether \code{NA} values should be removed from the frequency table. The header will always print the amount of \code{NA}s.}
 
 \item{row.names}{a logical value indicating whether row indices should be printed as \code{1:nrow(x)}}
 
@@ -46,25 +50,28 @@ A \code{data.frame} with an additional class \code{"frequency_tbl"}
 Create a frequency table of a vector with items or a data frame. Supports quasiquotation and markdown for reports. \code{top_freq} can be used to get the top/bottom \emph{n} items of a frequency table, with counts as names.
 }
 \details{
-This package also has a vignette available about this function, run: \code{browseVignettes("AMR")} to read it.
+Frequency tables (or frequency distributions) are summaries of the distribution of values in a sample. With the `freq` function, you can create univariate frequency tables. Multiple variables will be pasted into one variable, so it forces a univariate distribution. This package also has a vignette available to explain the use of this function further, run \code{browseVignettes("AMR")} to read it.
 
-For numeric values of any class, these additional values will be calculated and shown into the header:
+For numeric values of any class, these additional values will all be calculated with \code{na.rm = TRUE} and shown into the header:
 \itemize{
   \item{Mean, using \code{\link[base]{mean}}}
-  \item{Standard deviation, using \code{\link[stats]{sd}}}
+  \item{Standard Deviation, using \code{\link[stats]{sd}}}
-  \item{Five numbers of Tukey (min, Q1, median, Q3, max), using \code{\link[stats]{fivenum}}}
+  \item{Coefficient of Variation (CV), the standard deviation divided by the mean}
-  \item{Outliers (total count and unique count), using \code{\link{boxplot.stats}}}
+  \item{Mean Absolute Deviation (MAD), using \code{\link[stats]{mad}}}
-  \item{Coefficient of variation (CV), the standard deviation divided by the mean}
+  \item{Tukey Five-Number Summaries (minimum, Q1, median, Q3, maximum), using \code{\link[stats]{fivenum}}}
-  \item{Coefficient of quartile variation (CQV, sometimes called coefficient of dispersion), calculated as \code{(Q3 - Q1) / (Q3 + Q1)} using \code{\link{quantile}} with \code{type = 6} as quantile algorithm to comply with SPSS standards}
+  \item{Interquartile Range (IQR) calculated as \code{Q3 - Q1} using the Tukey Five-Number Summaries, i.e. \strong{not} using the \code{\link[stats]{quantile}} function}
+  \item{Coefficient of Quartile Variation (CQV, sometimes called coefficient of dispersion), calculated as \code{(Q3 - Q1) / (Q3 + Q1)} using the Tukey Five-Number Summaries}
+  \item{Outliers (total count and unique count), using \code{\link[grDevices]{boxplot.stats}}}
 }
 
-For dates and times of any class, these additional values will be calculated and shown into the header:
+For dates and times of any class, these additional values will be calculated with \code{na.rm = TRUE} and shown into the header:
 \itemize{
   \item{Oldest, using \code{\link[base]{min}}}
   \item{Newest, using \code{\link[base]{max}}, with difference between newest and oldest}
   \item{Median, using \code{\link[stats]{median}}, with percentage since oldest}
 }
 
+
 The function \code{top_freq} uses \code{\link[dplyr]{top_n}} internally and will include more than \code{n} rows if there are ties.
 }
 \examples{
@@ -95,17 +102,24 @@ septic_patients \%>\%
   filter(hospital_id == "A") \%>\%
   freq(genus, species)
 
-# save frequency table to an object
-years <- septic_patients \%>\%
-  mutate(year = format(date, "\%Y")) \%>\%
-  freq(year)
-years \%>\% pull(item)
-
 # get top 10 bugs of hospital A as a vector
 septic_patients \%>\%
   filter(hospital_id == "A") \%>\%
   freq(bactid) \%>\%
   top_freq(10)
+
+# save frequency table to an object
+years <- septic_patients \%>\%
+  mutate(year = format(date, "\%Y")) \%>\%
+  freq(year)
+
+# print only top 5
+years \%>\% print(nmax = 5)
+
+# transform to plain data.frame
+septic_patients \%>\%
+  freq(age) \%>\%
+  as.data.frame()
 }
 \keyword{freq}
 \keyword{frequency}

man/print.Rd

@@ -1,15 +1,12 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/freq.R, R/print.R
+% Please edit documentation in R/print.R
-\name{print.frequency_tbl}
+\name{print}
-\alias{print.frequency_tbl}
 \alias{print}
 \alias{print.tbl_df}
 \alias{print.tbl}
 \alias{print.data.table}
 \title{Printing Data Tables and Tibbles}
 \usage{
-\method{print}{frequency_tbl}(x, ...)
-
 \method{print}{tbl_df}(x, nmax = 10, header = TRUE, row.names = TRUE,
   right = FALSE, width = 1, na = "<NA>", ...)
 
@@ -20,8 +17,6 @@
 \arguments{
 \item{x}{object of class \code{data.frame}.}
 
-\item{...}{optional arguments to \code{print} or \code{plot} methods.}
-
 \item{nmax}{amount of rows to print in total. When the total amount of rows exceeds this limit, the first and last \code{nmax / 2} rows will be printed. Use \code{nmax = NA} to print all rows.}
 
 \item{header}{print header with information about data size and tibble grouping}
@@ -36,6 +31,8 @@
 
 \item{na}{value to print instead of NA}
 
+\item{...}{optional arguments to \code{print} or \code{plot} methods.}
+
 \item{print.keys}{print keys for \code{data.table}}
 }
 \description{

vignettes/freq.R

@@ -1,89 +0,0 @@
-## ----setup, include = FALSE, results = 'markup'--------------------------
-knitr::opts_chunk$set(
-  collapse = TRUE,
-  comment = "#"
-)
-library(dplyr)
-library(AMR)
-
-## ---- echo = TRUE, results = 'hide'--------------------------------------
-# just using base R
-freq(septic_patients$sex)
-
-# using base R to select the variable and pass it on with a pipe from the dplyr package
-septic_patients$sex %>% freq()
-
-# do it all with pipes, using the `select` function from the dplyr package
-septic_patients %>%
-  select(sex) %>%
-  freq()
-
-# or the preferred way: using a pipe to pass the variable on to the freq function
-septic_patients %>% freq(sex) # this also shows 'age' in the title
-
-
-## ---- echo = TRUE--------------------------------------------------------
-freq(septic_patients$sex)
-
-## ---- echo = TRUE, results = 'hide'--------------------------------------
-my_patients <- septic_patients %>% left_join_microorganisms()
-
-## ---- echo = TRUE--------------------------------------------------------
-colnames(microorganisms)
-
-## ---- echo = TRUE--------------------------------------------------------
-dim(septic_patients)
-dim(my_patients)
-
-## ---- echo = TRUE--------------------------------------------------------
-my_patients %>% freq(genus, species)
-
-## ---- echo = TRUE--------------------------------------------------------
-# # get age distribution of unique patients
-septic_patients %>% 
-  distinct(patient_id, .keep_all = TRUE) %>% 
-  freq(age, nmax = 5)
-
-## ---- echo = TRUE--------------------------------------------------------
-septic_patients %>%
-  freq(hospital_id)
-
-## ---- echo = TRUE--------------------------------------------------------
-septic_patients %>%
-  freq(hospital_id, sort.count = TRUE)
-
-## ---- echo = TRUE--------------------------------------------------------
-septic_patients %>%
-  select(amox) %>% 
-  freq()
-
-## ---- echo = TRUE--------------------------------------------------------
-septic_patients %>%
-  select(date) %>% 
-  freq(nmax = 5)
-
-## ---- echo = TRUE--------------------------------------------------------
-my_df <- septic_patients %>% freq(age)
-class(my_df)
-
-## ---- echo = TRUE--------------------------------------------------------
-dim(my_df)
-
-## ---- echo = TRUE--------------------------------------------------------
-septic_patients %>%
-  freq(amox, na.rm = FALSE)
-
-## ---- echo = TRUE--------------------------------------------------------
-septic_patients %>%
-  freq(hospital_id, row.names = FALSE)
-
-## ---- echo = TRUE--------------------------------------------------------
-septic_patients %>%
-  freq(hospital_id, markdown = TRUE)
-
-## ---- echo = FALSE-------------------------------------------------------
-# this will print "2018" in 2018, and "2018-yyyy" after 2018.
-yrs <- c(2018:format(Sys.Date(), "%Y"))
-yrs <- c(min(yrs), max(yrs))
-yrs <- paste(unique(yrs), collapse = "-")
-