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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
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# SOURCE #
# https://gitlab.com/msberends/AMR #
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# #
# LICENCE #
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# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
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# #
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# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# #
# This R package was created for academic research and was publicly #
# released in the hope that it will be useful, but it comes WITHOUT #
# ANY WARRANTY OR LIABILITY. #
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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
#' Frequency table
#'
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#' Create a frequency table of a vector with items or a \code{data.frame}. Supports quasiquotation and markdown for reports. Best practice is: \code{data \%>\% freq(var)}.\cr
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#' \code{top_freq} can be used to get the top/bottom \emph{n} items of a frequency table, with counts as names.
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#' @param x vector of any class or a \code{\link{data.frame}}, \code{\link{tibble}} (may contain a grouping variable) or \code{\link{table}}
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#' @param ... up to nine different columns of \code{x} when \code{x} is a \code{data.frame} or \code{tibble}, to calculate frequencies from - see Examples. Also supports quasiquotion.
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#' @param sort.count sort on count, i.e. frequencies. This will be \code{TRUE} at default for everything except when using grouping variables.
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#' @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.
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#' @param na.rm a logical value indicating whether \code{NA} values should be removed from the frequency table. The header (if set) will always print the amount of \code{NA}s.
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#' @param row.names a logical value indicating whether row indices should be printed as \code{1:nrow(x)}
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#' @param markdown a logical value indicating whether the frequency table should be printed in markdown format. This will print all rows (except when \code{nmax} is defined) and is default behaviour in non-interactive R sessions (like when knitting RMarkdown files).
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#' @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")})
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#' @param quote a logical value indicating whether or not strings should be printed with surrounding quotes
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#' @param header a logical value indicating whether an informative header should be printed
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#' @param title text to show above frequency table, at default to tries to coerce from the variables passed to \code{x}
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#' @param na a character string that should be used to show empty (\code{NA}) values (only useful when \code{na.rm = FALSE})
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#' @param droplevels a logical value indicating whether in factors empty levels should be dropped
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#' @param sep a character string to separate the terms when selecting multiple columns
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#' @inheritParams base::format
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#' @param f a frequency table
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#' @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.
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#' @param property property in header to return this value directly
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#' @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.
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#'
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#' For numeric values of any class, these additional values will all be calculated with \code{na.rm = TRUE} and shown into the header:
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#' \itemize{
#' \item{Mean, using \code{\link[base]{mean}}}
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#' \item{Standard Deviation, using \code{\link[stats]{sd}}}
#' \item{Coefficient of Variation (CV), the standard deviation divided by the mean}
#' \item{Mean Absolute Deviation (MAD), using \code{\link[stats]{mad}}}
#' \item{Tukey Five-Number Summaries (minimum, Q1, median, Q3, maximum), using \code{\link[stats]{fivenum}}}
#' \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}}}
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#' }
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#'
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#' For dates and times of any class, these additional values will be calculated with \code{na.rm = TRUE} and shown into the header:
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#' \itemize{
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#' \item{Oldest, using \code{\link{min}}}
#' \item{Newest, using \code{\link{max}}, with difference between newest and oldest}
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#' \item{Median, using \code{\link[stats]{median}}, with percentage since oldest}
#' }
#'
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#' In factors, all factor levels that are not existing in the input data will be dropped.
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#'
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#' The function \code{top_freq} uses \code{\link[dplyr]{top_n}} internally and will include more than \code{n} rows if there are ties.
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#' @importFrom stats fivenum sd mad
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#' @importFrom grDevices boxplot.stats
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#' @importFrom dplyr %>% arrange arrange_at bind_cols desc filter_at funs group_by mutate mutate_at n n_distinct pull select summarise tibble ungroup vars all_vars
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#' @importFrom utils browseVignettes
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#' @importFrom hms is.hms
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#' @importFrom crayon red green silver
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#' @importFrom rlang enquos eval_tidy as_label
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#' @keywords summary summarise frequency freq
#' @rdname freq
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#' @name freq
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#' @return A \code{data.frame} (with an additional class \code{"frequency_tbl"}) with five columns: \code{item}, \code{count}, \code{percent}, \code{cum_count} and \code{cum_percent}.
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#' @export
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#' @inheritSection AMR Read more on our website!
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#' @examples
#' library(dplyr)
#'
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#' # this all gives the same result:
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#' freq(septic_patients$hospital_id)
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#' freq(septic_patients[, "hospital_id"])
#' septic_patients$hospital_id %>% freq()
#' septic_patients[, "hospital_id"] %>% freq()
#' septic_patients %>% freq("hospital_id")
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#' septic_patients %>% freq(hospital_id) #<- easiest to remember (tidyverse)
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#'
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#'
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#' # you could also use `select` or `pull` to get your variables
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#' septic_patients %>%
#' filter(hospital_id == "A") %>%
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#' select(mo) %>%
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#' freq()
#'
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#'
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#' # multiple selected variables will be pasted together
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#' septic_patients %>%
#' left_join_microorganisms %>%
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#' freq(genus, species)
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#'
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#' # functions as quasiquotation are also supported
#' septic_patients %>%
#' freq(mo_genus(mo), mo_species(mo))
#'
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#'
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#' # group a variable and analyse another
#' septic_patients %>%
#' group_by(hospital_id) %>%
#' freq(gender)
#'
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#'
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#' # get top 10 bugs of hospital A as a vector
#' septic_patients %>%
#' filter(hospital_id == "A") %>%
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#' freq(mo) %>%
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#' top_freq(10)
#'
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#'
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#' # save frequency table to an object
#' years <- septic_patients %>%
#' mutate(year = format(date, "%Y")) %>%
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#' freq(year)
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#'
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#'
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#' # show only the top 5
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#' years %>% print(nmax = 5)
#'
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#'
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#' # save to an object with formatted percentages
#' years <- format(years)
#'
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#'
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#' # print a histogram of numeric values
#' septic_patients %>%
#' freq(age) %>%
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#' hist()
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#'
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#'
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#' # or print all points to a regular plot
#' septic_patients %>%
#' freq(age) %>%
#' plot()
#'
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#'
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#' # transform to a data.frame or tibble
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#' septic_patients %>%
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#' freq(age) %>%
#' as.data.frame()
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#'
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#'
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#' # or transform (back) to a vector
#' septic_patients %>%
#' freq(age) %>%
#' as.vector()
#'
#' identical(septic_patients %>%
#' freq(age) %>%
#' as.vector() %>%
#' sort(),
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#' sort(septic_patients$age)) # TRUE
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#'
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#'
#' # it also supports `table` objects
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#' table(septic_patients$gender,
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#' septic_patients$age) %>%
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#' freq(sep = " **sep** ")
#'
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#'
#' # only get selected columns
#' septic_patients %>%
#' freq(hospital_id) %>%
#' select(item, percent)
#'
#' septic_patients %>%
#' freq(hospital_id) %>%
#' select(-count, -cum_count)
#'
#'
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#' # check differences between frequency tables
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#' diff(freq(septic_patients$TMP),
#' freq(septic_patients$SXT))
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frequency_tbl <- function ( x ,
... ,
sort.count = TRUE ,
nmax = getOption ( " max.print.freq" ) ,
na.rm = TRUE ,
row.names = TRUE ,
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markdown = ! interactive ( ) ,
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digits = 2 ,
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quote = FALSE ,
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header = TRUE ,
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title = NULL ,
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na = " <NA>" ,
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droplevels = TRUE ,
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sep = " " ,
decimal.mark = getOption ( " OutDec" ) ,
big.mark = ifelse ( decimal.mark != " ," , " ," , " ." ) ) {
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mult.columns <- 0
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x.group = character ( 0 )
df <- NULL
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x.name <- NULL
cols <- NULL
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cols.names <- NULL
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if ( any ( class ( x ) == " list" ) ) {
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cols <- names ( x )
x <- as.data.frame ( x , stringsAsFactors = FALSE )
x.name <- " a list"
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} else if ( any ( class ( x ) == " matrix" ) ) {
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x <- as.data.frame ( x , stringsAsFactors = FALSE )
x.name <- " a matrix"
cols <- colnames ( x )
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if ( all ( cols %like% " V[0-9]" ) ) {
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cols <- NULL
}
}
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if ( any ( class ( x ) == " data.frame" ) ) {
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if ( is.null ( x.name ) ) {
x.name <- deparse ( substitute ( x ) )
}
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if ( x.name %like% " (%>%)" ) {
x.name <- x.name %>% strsplit ( " %>%" , fixed = TRUE ) %>% unlist ( ) %>% .[1 ] %>% trimws ( )
}
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if ( x.name == " ." ) {
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x.name <- " a data.frame"
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} else {
x.name <- paste0 ( " `" , x.name , " `" )
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}
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x.name.dims <- x %>%
dim ( ) %>%
format ( decimal.mark = decimal.mark , big.mark = big.mark ) %>%
trimws ( ) %>%
paste ( collapse = " x " )
x.name <- paste0 ( x.name , " (" , x.name.dims , " )" )
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x.group <- group_vars ( x )
if ( length ( x.group ) > 1 ) {
x.group <- x.group [1L ]
warning ( " freq supports one grouping variable, only `" , x.group , " ` will be kept." , call. = FALSE )
}
user_exprs <- enquos ( ... )
if ( length ( user_exprs ) > 0 ) {
new_list <- list ( 0 )
for ( i in 1 : length ( user_exprs ) ) {
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new_list [ [i ] ] <- tryCatch ( eval_tidy ( user_exprs [ [i ] ] , data = x ) ,
error = function ( e ) stop ( e $ message , call. = FALSE ) )
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if ( length ( new_list [ [i ] ] ) == 1 ) {
if ( is.character ( new_list [ [i ] ] ) & new_list [ [i ] ] %in% colnames ( x ) ) {
# support septic_patients %>% freq("hospital_id")
new_list [ [i ] ] <- x %>% pull ( new_list [ [i ] ] )
}
}
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cols <- c ( cols , as_label ( user_exprs [ [i ] ] ) )
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}
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if ( length ( new_list ) == 1 & length ( x.group ) == 0 ) {
# is now character
x <- new_list [ [1 ] ]
df <- NULL
} else {
# create data frame
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df <- as.data.frame ( new_list , col.names = cols , stringsAsFactors = FALSE )
cols.names <- colnames ( df )
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}
} else {
# complete data frame
df <- x
}
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# support grouping variables
if ( length ( x.group ) > 0 ) {
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x.group_cols <- c ( x.group , cols.names )
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x <- bind_cols ( x , df )
# if (droplevels == TRUE) {
# x <- x %>% mutate_at(vars(x.group_cols), droplevels)
# }
suppressWarnings (
df <- x %>%
group_by_at ( vars ( x.group_cols ) ) %>%
summarise ( count = n ( ) )
)
if ( na.rm == TRUE ) {
df <- df %>% filter_at ( vars ( x.group_cols ) , all_vars ( ! is.na ( .) ) )
}
if ( ! missing ( sort.count ) ) {
if ( sort.count == TRUE ) {
df <- df %>% arrange_at ( c ( x.group_cols , " count" ) , desc )
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}
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}
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df <- df %>%
mutate ( cum_count = cumsum ( count ) )
df.topleft <- df [1 , 1 ]
df <- df %>%
ungroup ( ) %>%
# do not repeat group labels
mutate_at ( vars ( x.group ) , funs ( ifelse ( lag ( .) == ., " " , .) ) )
df [1 , 1 ] <- df.topleft
colnames ( df ) [1 : 2 ] <- c ( " group" , " item" )
if ( ! is.null ( levels ( df $ item ) ) & droplevels == TRUE ) {
# is factor
df <- df %>% filter ( count != 0 )
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}
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} else {
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if ( ! is.null ( df ) ) {
# no groups, multiple values like: septic_patients %>% freq(mo, mo_genus(mo))
x <- df
df <- NULL
}
}
if ( length ( cols ) > 0 & is.data.frame ( x ) ) {
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x <- x [ , cols.names ]
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}
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} else if ( any ( class ( x ) == " table" ) ) {
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x <- as.data.frame ( x , stringsAsFactors = FALSE )
# now this DF contains 3 columns: the 2 vars and a Freq column
# paste the first 2 cols and repeat them Freq times:
x <- rep ( x = do.call ( paste , c ( x [colnames ( x ) [1 : 2 ] ] , sep = sep ) ) ,
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times = x $ Freq )
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x.name <- " a `table` object"
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cols <- NULL
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# mult.columns <- 2
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} else {
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x.name <- deparse ( substitute ( x ) )
if ( x.name %like% " [$]" ) {
cols <- unlist ( strsplit ( x.name , " $" , fixed = TRUE ) ) [2 ]
x.name <- unlist ( strsplit ( x.name , " $" , fixed = TRUE ) ) [1 ]
# try to find the object to determine dimensions
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x.obj <- tryCatch ( get ( x.name ) , error = function ( e ) NULL )
x.name <- paste0 ( " `" , x.name , " `" )
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if ( ! is.null ( dim ( x.obj ) ) ) {
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x.name <- paste0 ( x.name ,
" (" ,
x.obj %>%
dim ( ) %>%
format ( decimal.mark = decimal.mark , big.mark = big.mark ) %>%
trimws ( ) %>%
paste ( collapse = " x " ) ,
" )" )
}
} else {
x.name <- NULL
cols <- NULL
}
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}
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if ( ! is.null ( ncol ( x ) ) ) {
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if ( ncol ( x ) == 1 & any ( class ( x ) == " data.frame" ) ) {
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x <- x %>% pull ( 1 )
} else if ( ncol ( x ) < 10 ) {
mult.columns <- ncol ( x )
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# paste old columns together
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x <- do.call ( paste , c ( x [colnames ( x ) ] , sep = sep ) )
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} else {
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stop ( " A maximum of 9 columns can be analysed at the same time." , call. = FALSE )
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}
}
if ( mult.columns > 1 ) {
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NAs <- x [is.na ( x ) | x == trimws ( strrep ( " NA " , mult.columns ) ) ]
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} else {
NAs <- x [is.na ( x ) ]
}
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if ( mult.columns > 0 ) {
header_list <- list ( columns = mult.columns )
} else {
header_list <- list ( class = class ( x ) ,
mode = mode ( x ) )
}
header_list $ length <- length ( x )
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if ( na.rm == TRUE ) {
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x_class <- class ( x )
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x <- x [ ! x %in% NAs ]
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class ( x ) <- x_class
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}
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markdown_line <- " "
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if ( markdown == TRUE ) {
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markdown_line <- " "
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}
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x_align <- " l"
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if ( ! is.null ( levels ( x ) ) ) {
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header_list $ levels <- levels ( x )
header_list $ ordered <- is.ordered ( x )
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# drop levels of non-existing factor values,
# since dplyr >= 0.8.0 does not do this anymore in group_by
if ( droplevels == TRUE ) {
x <- droplevels ( x )
}
}
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header_list $ na_length <- length ( NAs )
header_list $ unique <- n_distinct ( x )
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if ( NROW ( x ) > 0 & any ( class ( x ) == " character" ) ) {
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header_list $ shortest <- x %>% base :: nchar ( ) %>% base :: min ( na.rm = TRUE )
header_list $ longest <- x %>% base :: nchar ( ) %>% base :: max ( na.rm = TRUE )
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}
if ( NROW ( x ) > 0 & any ( class ( x ) == " mo" ) ) {
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x_mo <- as.mo ( x ) # do it once for all three
header_list $ families <- x_mo %>% mo_family ( ) %>% n_distinct ( )
header_list $ genera <- x_mo %>% mo_genus ( ) %>% n_distinct ( )
header_list $ species <- x_mo %>% mo_species ( ) %>% n_distinct ( )
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}
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if ( NROW ( x ) > 0 & any ( class ( x ) == " difftime" ) & ! is.hms ( x ) ) {
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header_list $ units <- attributes ( x ) $ units
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x <- as.double ( x )
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# after this, the numeric header_txt continues
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}
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if ( NROW ( x ) > 0 & any ( class ( x ) %in% c ( " double" , " integer" , " numeric" , " raw" , " single" ) ) ) {
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# right align number
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x_align <- " r"
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header_list $ mean <- base :: mean ( x , na.rm = TRUE )
header_list $ sd <- stats :: sd ( x , na.rm = TRUE )
header_list $ cv <- cv ( x , na.rm = TRUE )
header_list $ mad <- stats :: mad ( x , na.rm = TRUE )
Tukey_five <- stats :: fivenum ( x , na.rm = TRUE )
header_list $ fivenum <- Tukey_five
header_list $ IQR <- Tukey_five [4 ] - Tukey_five [2 ]
header_list $ cqv <- cqv ( x , na.rm = TRUE )
header_list $ outliers_total <- length ( boxplot.stats ( x ) $ out )
header_list $ outliers_unique <- n_distinct ( boxplot.stats ( x ) $ out )
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}
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if ( any ( class ( x ) == " rsi" ) ) {
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header_list $ count_SI <- max ( 0 , sum ( x %in% c ( " S" , " I" ) , na.rm = TRUE ) , na.rm = TRUE )
header_list $ count_R <- max ( 0 , sum ( x == " R" , na.rm = TRUE ) , na.rm = TRUE )
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}
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formatdates <- " %e %B %Y" # = d mmmm yyyy
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if ( is.hms ( x ) ) {
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x <- x %>% as.POSIXlt ( )
formatdates <- " %H:%M:%S"
}
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if ( NROW ( x ) > 0 & any ( class ( x ) %in% c ( " Date" , " POSIXct" , " POSIXlt" ) ) ) {
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if ( formatdates == " %H:%M:%S" ) {
# hms
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header_list $ earliest <- min ( x , na.rm = TRUE )
header_list $ latest <- max ( x , na.rm = TRUE )
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} else {
# other date formats
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header_list $ oldest <- min ( x , na.rm = TRUE )
header_list $ newest <- max ( x , na.rm = TRUE )
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}
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header_list $ median <- median ( x , na.rm = TRUE )
header_list $ date_format <- formatdates
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}
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if ( any ( class ( x ) == " POSIXlt" ) ) {
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x <- x %>% format ( formatdates )
}
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nmax.set <- ! missing ( nmax )
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if ( ! nmax.set & is.null ( nmax ) & is.null ( base :: getOption ( " max.print.freq" , default = NULL ) ) ) {
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# default for max print setting
nmax <- 15
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} else if ( is.null ( nmax ) ) {
nmax <- length ( x )
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}
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if ( nmax %in% c ( 0 , Inf , NA , NULL ) ) {
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nmax <- length ( x )
}
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column_names <- c ( " Item" , " Count" , " Percent" , " Cum. Count" , " Cum. Percent" )
column_names_df <- c ( " item" , " count" , " percent" , " cum_count" , " cum_percent" )
column_align <- c ( x_align , " r" , " r" , " r" , " r" )
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if ( is.null ( df ) ) {
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suppressWarnings ( # suppress since dplyr 0.8.0, which idiotly warns about included NAs :(
# create table with counts and percentages
df <- tibble ( item = x ) %>%
group_by ( item ) %>%
summarise ( count = n ( ) )
)
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# sort according to setting
if ( sort.count == TRUE ) {
df <- df %>% arrange ( desc ( count ) , item )
} else {
df <- df %>% arrange ( item )
}
} else {
column_names <- c ( " Group" , column_names )
column_names_df <- c ( " group" , column_names_df )
column_align <- c ( " l" , column_align )
}
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if ( df $ item %>% paste ( collapse = " ," ) %like% " \033" ) {
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# remove escape char
# see https://en.wikipedia.org/wiki/Escape_character#ASCII_escape_character
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df <- df %>% mutate ( item = item %>% gsub ( " \033" , " " , ., fixed = TRUE ) )
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}
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if ( quote == TRUE ) {
df $ item <- paste0 ( ' "' , df $ item , ' "' )
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if ( length ( x.group ) != 0 ) {
df $ group <- paste0 ( ' "' , df $ group , ' "' )
}
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}
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df <- as.data.frame ( df , stringsAsFactors = FALSE )
df $ percent <- df $ count / base :: sum ( df $ count , na.rm = TRUE )
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if ( length ( x.group ) == 0 ) {
df $ cum_count <- base :: cumsum ( df $ count )
}
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df $ cum_percent <- df $ cum_count / base :: sum ( df $ count , na.rm = TRUE )
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if ( length ( x.group ) != 0 ) {
# sort columns
df <- df [ , column_names_df ]
}
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if ( markdown == TRUE ) {
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tbl_format <- " markdown"
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} else {
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tbl_format <- " pandoc"
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}
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if ( ! is.null ( title ) ) {
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title <- trimws ( gsub ( " ^Frequency table of" , " " , title [1L ] , ignore.case = TRUE ) )
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}
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# if (nmax.set == FALSE) {
# nmax <- nrow(df)
# }
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structure ( .Data = df ,
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class = c ( " frequency_tbl" , class ( df ) ) ,
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header = header_list ,
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opt = list ( title = title ,
data = x.name ,
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vars = cols ,
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group_var = x.group ,
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header = header ,
row_names = row.names ,
column_names = column_names ,
column_align = column_align ,
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decimal.mark = decimal.mark ,
big.mark = big.mark ,
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tbl_format = tbl_format ,
na = na ,
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digits = digits ,
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nmax = nmax ,
nmax.set = nmax.set ) )
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}
#' @rdname freq
#' @export
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freq <- frequency_tbl
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#' @importFrom crayon silver green red
#' @importFrom dplyr %>%
format_header <- function ( x , markdown = FALSE , decimal.mark = " ." , big.mark = " ," , digits = 2 ) {
newline <- " \n"
if ( markdown == TRUE ) {
newline <- " \n"
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# no colours in markdown
silver <- function ( x ) x
green <- function ( x ) x
red <- function ( x ) x
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}
header <- header ( x )
x_class <- header $ class
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has_length <- header $ length > 0
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# FORMATTING
# rsi
if ( has_length == TRUE & any ( x_class == " rsi" ) ) {
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if ( ! is.null ( attributes ( x ) $ opt $ vars ) ) {
ab <- tryCatch ( as.ab ( attributes ( x ) $ opt $ vars ) , error = function ( e ) NA )
if ( ! is.na ( ab ) & isTRUE ( length ( ab ) > 0 ) ) {
header $ drug <- paste0 ( ab_name ( ab [1L ] ) , " (" , ab [1L ] , " , " , ab_atc ( ab [1L ] ) , " )" )
header $ group <- ab_group ( ab [1L ] )
}
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}
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header $ `%SI` <- percent ( header $ count_SI / ( header $ count_SI + header $ count_R ) ,
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force_zero = TRUE , round = digits , decimal.mark = decimal.mark )
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}
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header <- header [ ! names ( header ) %in% c ( " count_SI" , " count_R" ) ]
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# dates
if ( ! is.null ( header $ date_format ) ) {
if ( header $ date_format == " %H:%M:%S" ) {
header $ median <- paste0 ( format ( header $ median , header $ date_format ) ,
" (" ,
( as.double ( difftime ( header $ median , header $ earliest , units = " auto" ) ) /
as.double ( difftime ( header $ latest , header $ earliest , units = " auto" ) ) ) %>%
percent ( round = digits , decimal.mark = decimal.mark ) , " )" )
header $ latest <- paste0 ( format ( header $ latest , header $ date_format ) ,
" (+" ,
difftime ( header $ latest , header $ earliest , units = " mins" ) %>%
as.double ( ) %>%
format ( digits = digits , decimal.mark = decimal.mark , big.mark = big.mark ) ,
" min.)" )
header $ earliest <- format ( header $ earliest , header $ date_format )
header $ median <- trimws ( header $ median )
header $ latest <- trimws ( header $ latest )
header $ earliest <- trimws ( header $ earliest )
} else {
header $ median <- paste0 ( format ( header $ median , header $ date_format ) ,
" (" ,
( as.double ( difftime ( header $ median , header $ oldest , units = " auto" ) ) /
as.double ( difftime ( header $ newest , header $ oldest , units = " auto" ) ) ) %>%
percent ( round = digits , decimal.mark = decimal.mark ) , " )" )
header $ newest <- paste0 ( format ( header $ newest , header $ date_format ) ,
" (+" ,
difftime ( header $ newest , header $ oldest , units = " auto" ) %>%
as.double ( ) %>%
format ( digits = digits , decimal.mark = decimal.mark , big.mark = big.mark ) ,
" )" )
header $ oldest <- format ( header $ oldest , header $ date_format )
header $ median <- trimws ( header $ median )
header $ newest <- trimws ( header $ newest )
header $ oldest <- trimws ( header $ oldest )
}
header <- header [names ( header ) != " date_format" ]
}
# class and mode
if ( is.null ( header $ columns ) ) {
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# if (markdown == TRUE) {
# header$class <- paste0("`", header$class, "`")
# }
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if ( ! header $ mode %in% header $ class ) {
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# if (markdown == TRUE) {
# header$mode <- paste0("`", header$mode, "`")
# }
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header $ class <- header $ class %>% rev ( ) %>% paste ( collapse = " > " ) %>% paste0 ( silver ( paste0 ( " (" , header $ mode , " )" ) ) )
} else {
header $ class <- header $ class %>% rev ( ) %>% paste ( collapse = " > " )
}
header <- header [names ( header ) != " mode" ]
}
# levels
if ( ! is.null ( header $ levels ) ) {
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# if (markdown == TRUE) {
# header$levels <- paste0("`", header$levels, "`")
# }
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if ( header $ ordered == TRUE ) {
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levels_text <- paste0 ( header $ levels , collapse = " < " )
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} else {
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levels_text <- paste0 ( header $ levels , collapse = " , " )
}
if ( nchar ( levels_text ) > 70 ) {
# levels text wider than half the console
levels_text <- paste0 ( substr ( levels_text , 1 , 70 - 3 ) , " ..." )
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if ( nchar ( gsub ( " [^`]" , " " , levels_text ) ) %% 2 == 1 ) {
# odd number of backticks, should be even
levels_text <- paste0 ( levels_text , " `" )
}
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}
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header $ levels <- paste0 ( length ( header $ levels ) , " : " , levels_text )
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header <- header [names ( header ) != " ordered" ]
}
# length and NAs
if ( has_length == TRUE ) {
na_txt <- paste0 ( header $ na_length %>% format ( decimal.mark = decimal.mark , big.mark = big.mark ) , " = " ,
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( header $ na_length / header $ length ) %>% percent ( force_zero = TRUE , round = digits , decimal.mark = decimal.mark ) %>%
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sub ( " NaN" , " 0" , ., fixed = TRUE ) )
if ( ! na_txt %like% " ^0 =" ) {
na_txt <- red ( na_txt )
} else {
na_txt <- green ( na_txt )
}
na_txt <- paste0 ( " (of which NA: " , na_txt , " )" )
} else {
na_txt <- " "
}
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header $ length <- paste ( format ( header $ length , decimal.mark = decimal.mark , big.mark = big.mark ) ,
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na_txt )
header <- header [names ( header ) != " na_length" ]
# format all numeric values
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header <- lapply ( header , function ( x ) {
if ( is.numeric ( x ) ) {
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if ( any ( x < 1000 , na.rm = TRUE ) ) {
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format ( round2 ( x , digits = digits ) , decimal.mark = decimal.mark , big.mark = big.mark )
} else {
format ( x , digits = digits , decimal.mark = decimal.mark , big.mark = big.mark )
}
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} else {
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x
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}
} )
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# numeric values
if ( has_length == TRUE & any ( x_class %in% c ( " double" , " integer" , " numeric" , " raw" , " single" ) ) ) {
header $ sd <- paste0 ( header $ sd , " (CV: " , header $ cv , " , MAD: " , header $ mad , " )" )
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header $ fivenum <- paste0 ( paste ( trimws ( header $ fivenum ) , collapse = " | " ) , " (IQR: " , header $ IQR , " , CQV: " , header $ cqv , " )" )
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header $ outliers_total <- paste0 ( header $ outliers_total , " (unique count: " , header $ outliers_unique , " )" )
header <- header [ ! names ( header ) %in% c ( " cv" , " mad" , " IQR" , " cqv" , " outliers_unique" ) ]
}
# header names
header_names <- paste0 ( names ( header ) , " : " )
header_names <- gsub ( " sd" , " SD" , header_names )
header_names <- gsub ( " fivenum" , " Five-Num" , header_names )
header_names <- gsub ( " outliers_total" , " Outliers" , header_names )
# capitalise first character
header_names <- gsub ( " ^(.)" , " \\U\\1" , header_names , perl = TRUE )
# make all header captions equal size
header_names <- gsub ( " \\s" , " " , format ( header_names ,
width = max ( nchar ( header_names ) ,
na.rm = TRUE ) ) )
header <- paste0 ( header_names , header )
header <- paste ( header , collapse = newline )
# add newline after 'Unique'
gsub ( " (.*Unique.*\\n)(.*?)" , paste0 ( " \\1" , newline , " \\2" ) , header )
}
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#' @rdname freq
#' @export
#' @importFrom dplyr top_n pull
top_freq <- function ( f , n ) {
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if ( ! " frequency_tbl" %in% class ( f ) ) {
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stop ( " `top_freq` can only be applied to frequency tables" , call. = FALSE )
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}
if ( ! is.numeric ( n ) | length ( n ) != 1L ) {
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stop ( " For `top_freq`, 'n' must be a number of length 1" , call. = FALSE )
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}
top <- f %>% top_n ( n , count )
vect <- top %>% pull ( item )
names ( vect ) <- top %>% pull ( count )
if ( length ( vect ) > abs ( n ) ) {
message ( " top_freq: selecting " , length ( vect ) , " items instead of " , abs ( n ) , " , because of ties" )
}
vect
}
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#' @rdname freq
#' @export
header <- function ( f , property = NULL ) {
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if ( ! " frequency_tbl" %in% class ( f ) ) {
stop ( " `header` can only be applied to frequency tables" , call. = FALSE )
}
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if ( is.null ( property ) ) {
attributes ( f ) $ header
} else {
a <- attributes ( f ) $ header
if ( any ( property %in% names ( f ) ) ) {
a [names ( a ) %in% property ]
}
}
}
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#' @noRd
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#' @exportMethod diff.frequency_tbl
#' @importFrom dplyr %>% full_join mutate
#' @export
diff.frequency_tbl <- function ( x , y , ... ) {
# check classes
if ( ! " frequency_tbl" %in% class ( x )
| ! " frequency_tbl" %in% class ( y ) ) {
stop ( " Both x and y must be a frequency table." )
}
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cat ( " Differences between frequency tables" )
if ( identical ( x , y ) ) {
cat ( " \n\nNo differences found.\n" )
return ( invisible ( ) )
}
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x.attr <- attributes ( x ) $ opt
# only keep item and count
x <- x [ , 1 : 2 ]
y <- y [ , 1 : 2 ]
x <- x %>%
full_join ( y ,
by = colnames ( x ) [1 ] ,
suffix = c ( " .x" , " .y" ) ) %>%
mutate (
diff = case_when (
is.na ( count.y ) ~ - count.x ,
is.na ( count.x ) ~ count.y ,
TRUE ~ count.y - count.x ) ) %>%
mutate (
diff.percent = percent (
diff / count.x ,
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force_zero = TRUE ) ) %>%
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mutate ( diff = ifelse ( diff %like% " ^-" ,
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diff ,
paste0 ( " +" , diff ) ) ,
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diff.percent = ifelse ( diff.percent %like% " ^-" ,
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diff.percent ,
paste0 ( " +" , diff.percent ) ) )
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print (
knitr :: kable ( x ,
format = x.attr $ tbl_format ,
col.names = c ( " Item" , " Count #1" , " Count #2" , " Difference" , " Diff. percent" ) ,
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align = paste0 ( x.attr $ column_align [1 ] , " rrrr" ) ,
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padding = 1 )
)
}
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#' @rdname freq
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#' @exportMethod print.frequency_tbl
#' @importFrom knitr kable
#' @importFrom dplyr n_distinct
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#' @importFrom crayon bold silver
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#' @export
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print.frequency_tbl <- function ( x ,
nmax = getOption ( " max.print.freq" , default = 15 ) ,
markdown = ! interactive ( ) ,
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header = TRUE ,
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decimal.mark = getOption ( " OutDec" ) ,
big.mark = ifelse ( decimal.mark != " ," , " ," , " ." ) ,
... ) {
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opt <- attr ( x , " opt" )
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opt $ header_txt <- header ( x )
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dots <- list ( ... )
if ( " markdown" %in% names ( dots ) ) {
if ( dots $ markdown == TRUE ) {
opt $ tbl_format <- " markdown"
} else {
opt $ tbl_format <- " pandoc"
}
}
if ( ! missing ( markdown ) ) {
if ( markdown == TRUE ) {
opt $ tbl_format <- " markdown"
} else {
opt $ tbl_format <- " pandoc"
}
}
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if ( length ( opt $ vars ) == 0 ) {
opt $ vars <- NULL
}
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if ( is.null ( opt $ title ) ) {
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if ( isTRUE ( opt $ data %like% " ^a data.frame" ) & opt $ tbl_format == " markdown" ) {
opt $ data <- gsub ( " data.frame" , " `data.frame`" , opt $ data , fixed = TRUE )
}
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if ( ! is.null ( opt $ data ) & ! is.null ( opt $ vars ) ) {
title <- paste0 ( " `" , paste0 ( opt $ vars , collapse = " ` and `" ) , " ` from " , opt $ data )
} else if ( ! is.null ( opt $ data ) & is.null ( opt $ vars ) ) {
title <- opt $ data
} else if ( is.null ( opt $ data ) & ! is.null ( opt $ vars ) ) {
title <- paste0 ( " `" , paste0 ( opt $ vars , collapse = " ` and `" ) , " `" )
} else {
title <- " "
}
if ( title != " " & length ( opt $ group_var ) != 0 ) {
group_var <- paste0 ( " (grouped by `" , opt $ group_var , " `)" )
if ( opt $ tbl_format == " pandoc" ) {
group_var <- silver ( group_var )
}
title <- paste ( title , group_var )
}
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title <- trimws ( title )
if ( title == " " ) {
title <- " Frequency table"
} else {
title <- paste ( " Frequency table of" , trimws ( title ) )
}
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} else {
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title <- opt $ title
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}
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if ( ! missing ( nmax ) ) {
opt $ nmax <- nmax
opt $ nmax.set <- TRUE
}
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if ( opt $ nmax %in% c ( 0 , Inf , NA , NULL ) ) {
opt $ nmax <- NROW ( x )
opt $ nmax.set <- FALSE
} else if ( opt $ nmax >= NROW ( x ) ) {
opt $ nmax.set <- FALSE
}
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if ( ! missing ( decimal.mark ) ) {
opt $ decimal.mark <- decimal.mark
}
if ( ! missing ( big.mark ) ) {
opt $ big.mark <- big.mark
}
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if ( ! missing ( header ) ) {
opt $ header <- header
}
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# bold title
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if ( opt $ tbl_format == " pandoc" ) {
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title <- bold ( title )
} else if ( opt $ tbl_format == " markdown" ) {
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title <- paste0 ( " \n\n**" , title , " ** " ) # two space for newline
}
cat ( title , " \n\n" )
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if ( NROW ( x ) == 0 | isTRUE ( all ( is.na ( x $ item ) ) ) ) {
cat ( " No observations" )
if ( isTRUE ( all ( is.na ( x $ item ) ) ) ) {
cat ( " - all values are missing (<NA>)" )
}
cat ( " .\n" )
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if ( opt $ tbl_format == " markdown" ) {
cat ( " \n" )
}
return ( invisible ( ) )
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}
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if ( opt $ header == TRUE ) {
if ( ! is.null ( opt $ header_txt ) ) {
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if ( is.null ( opt $ digits ) ) {
opt $ digits <- 2
}
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cat ( format_header ( x , digits = opt $ digits , markdown = ( opt $ tbl_format == " markdown" ) ,
decimal.mark = decimal.mark , big.mark = big.mark ) )
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}
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}
# save old NA setting for kable
opt.old <- options ( ) $ knitr.kable.NA
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if ( is.null ( opt $ na ) ) {
opt $ na <- " <NA>"
}
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if ( opt $ tbl_format == " markdown" ) {
# no HTML tags
opt $ na <- gsub ( " <" , " (" , opt $ na , fixed = TRUE )
opt $ na <- gsub ( " >" , " )" , opt $ na , fixed = TRUE )
}
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options ( knitr.kable.NA = opt $ na )
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x.rows <- nrow ( x )
x.unprinted <- base :: sum ( x [ ( opt $ nmax + 1 ) : nrow ( x ) , " count" ] , na.rm = TRUE )
x.printed <- base :: sum ( x $ count ) - x.unprinted
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if ( nrow ( x ) > opt $ nmax & opt $ tbl_format != " markdown" ) {
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if ( opt $ nmax.set == TRUE ) {
nmax <- opt $ nmax
} else {
nmax <- getOption ( " max.print.freq" , default = 15 )
}
x <- x [1 : nmax , ]
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if ( opt $ nmax.set == TRUE ) {
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footer <- paste ( " [ reached `nmax = " , opt $ nmax , " `" , sep = " " )
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} else {
footer <- ' [ reached getOption("max.print.freq")'
}
footer <- paste ( footer ,
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" -- omitted " ,
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format ( x.rows - opt $ nmax , big.mark = opt $ big.mark , decimal.mark = opt $ decimal.mark ) ,
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" entries, n = " ,
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format ( x.unprinted , big.mark = opt $ big.mark , decimal.mark = opt $ decimal.mark ) ,
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" (" ,
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( x.unprinted / ( x.unprinted + x.printed ) ) %>% percent ( force_zero = TRUE , decimal.mark = opt $ decimal.mark ) ,
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" ) ]\n" , sep = " " )
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if ( opt $ tbl_format == " pandoc" ) {
footer <- silver ( footer ) # only silver in regular printing
}
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} else if ( opt $ tbl_format == " markdown" ) {
if ( opt $ nmax.set == TRUE ) {
x <- x [1 : opt $ nmax , ]
footer <- paste ( " \n(omitted " ,
format ( x.rows - opt $ nmax , big.mark = opt $ big.mark , decimal.mark = opt $ decimal.mark ) ,
" entries, n = " ,
format ( x.unprinted , big.mark = opt $ big.mark , decimal.mark = opt $ decimal.mark ) ,
" [" ,
( x.unprinted / ( x.unprinted + x.printed ) ) %>% percent ( force_zero = TRUE , decimal.mark = opt $ decimal.mark ) ,
" ])\n" , sep = " " )
} else {
footer <- NULL
}
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} else {
footer <- NULL
}
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if ( " item" %in% colnames ( x ) ) {
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if ( any ( class ( x $ item ) %in% c ( " double" , " integer" , " numeric" , " raw" , " single" ) ) ) {
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x $ item <- format ( x $ item , decimal.mark = opt $ decimal.mark , big.mark = opt $ big.mark )
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}
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} else {
opt $ column_names <- opt $ column_names [ ! opt $ column_names == " Item" ]
}
if ( " count" %in% colnames ( x ) ) {
if ( all ( x $ count == 1 ) ) {
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warning ( " All observations are unique." , call. = FALSE )
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}
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x $ count <- format ( x $ count , decimal.mark = opt $ decimal.mark , big.mark = opt $ big.mark )
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} else {
opt $ column_names <- opt $ column_names [ ! opt $ column_names == " Count" ]
}
if ( " percent" %in% colnames ( x ) ) {
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x $ percent <- percent ( x $ percent , force_zero = TRUE , decimal.mark = opt $ decimal.mark )
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} else {
opt $ column_names <- opt $ column_names [ ! opt $ column_names == " Percent" ]
}
if ( " cum_count" %in% colnames ( x ) ) {
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x $ cum_count <- format ( x $ cum_count , decimal.mark = opt $ decimal.mark , big.mark = opt $ big.mark )
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} else {
opt $ column_names <- opt $ column_names [ ! opt $ column_names == " Cum. Count" ]
}
if ( " cum_percent" %in% colnames ( x ) ) {
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x $ cum_percent <- percent ( x $ cum_percent , force_zero = TRUE , decimal.mark = opt $ decimal.mark )
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} else {
opt $ column_names <- opt $ column_names [ ! opt $ column_names == " Cum. Percent" ]
}
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if ( opt $ tbl_format == " markdown" ) {
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cat ( " \n" )
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}
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print (
knitr :: kable ( x ,
format = opt $ tbl_format ,
row.names = opt $ row_names ,
col.names = opt $ column_names ,
align = opt $ column_align ,
padding = 1 )
)
if ( ! is.null ( footer ) ) {
cat ( footer )
}
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if ( opt $ tbl_format == " markdown" ) {
cat ( " \n\n" )
} else {
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cat ( " \n" )
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}
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# reset old kable setting
options ( knitr.kable.NA = opt.old )
return ( invisible ( ) )
}
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#' @noRd
#' @exportMethod as.data.frame.frequency_tbl
#' @export
as.data.frame.frequency_tbl <- function ( x , ... ) {
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attr ( x , " package" ) <- NULL
attr ( x , " opt" ) <- NULL
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as.data.frame.data.frame ( x , ... )
}
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#' @exportMethod select.frequency_tbl
#' @export
#' @importFrom dplyr select
#' @noRd
select.frequency_tbl <- function ( .data , ... ) {
select ( as.data.frame ( .data ) , ... )
}
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#' @noRd
#' @exportMethod as_tibble.frequency_tbl
#' @export
#' @importFrom dplyr as_tibble
as_tibble.frequency_tbl <- function ( x , validate = TRUE , ... , rownames = NA ) {
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attr ( x , " package" ) <- NULL
attr ( x , " opt" ) <- NULL
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as_tibble ( x = as.data.frame ( x ) , validate = validate , ... , rownames = rownames )
}
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#' @noRd
#' @exportMethod hist.frequency_tbl
#' @export
#' @importFrom graphics hist
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hist.frequency_tbl <- function ( x , breaks = " Sturges" , main = NULL , xlab = NULL , ... ) {
opt <- attr ( x , " opt" )
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if ( ! class ( x $ item ) %in% c ( " numeric" , " double" , " integer" , " Date" ) ) {
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stop ( " `x` must be numeric or Date." , call. = FALSE )
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}
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if ( ! is.null ( opt $ vars ) ) {
title <- opt $ vars
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} else if ( ! is.null ( opt $ data ) ) {
title <- opt $ data
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} else {
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title <- " frequency table"
}
if ( class ( x $ item ) == " Date" ) {
x <- as.Date ( as.vector ( x ) , origin = " 1970-01-01" )
} else {
x <- as.vector ( x )
}
if ( is.null ( main ) ) {
main <- paste ( " Histogram of" , title )
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}
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if ( is.null ( xlab ) ) {
xlab <- title
}
hist ( x , main = main , xlab = xlab , breaks = breaks , ... )
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}
#' @noRd
#' @exportMethod plot.frequency_tbl
#' @export
plot.frequency_tbl <- function ( x , y , ... ) {
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opt <- attr ( x , " opt" )
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if ( ! is.null ( opt $ vars ) ) {
title <- opt $ vars
} else {
title <- " "
}
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plot ( x = x $ item , y = x $ count , ylab = " Count" , xlab = title , ... )
}
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#' @noRd
#' @exportMethod as.vector.frequency_tbl
#' @export
as.vector.frequency_tbl <- function ( x , mode = " any" ) {
as.vector ( rep ( x $ item , x $ count ) , mode = mode )
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}
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#' @noRd
#' @exportMethod format.frequency_tbl
#' @export
format.frequency_tbl <- function ( x , digits = 1 , ... ) {
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opt <- attr ( x , " opt" )
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if ( opt $ nmax.set == TRUE ) {
nmax <- opt $ nmax
} else {
nmax <- getOption ( " max.print.freq" , default = 15 )
}
x <- x [1 : nmax , ]
x $ percent <- percent ( x $ percent , round = digits , force_zero = TRUE )
x $ cum_percent <- percent ( x $ cum_percent , round = digits , force_zero = TRUE )
base :: format.data.frame ( x , ... )
}