mirror of https://github.com/msberends/AMR.git
1121 lines
38 KiB
R
Executable File
1121 lines
38 KiB
R
Executable File
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.com/msberends/AMR #
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# #
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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 #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# #
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# This R package was created for academic research and was publicly #
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# released in the hope that it will be useful, but it comes WITHOUT #
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# ANY WARRANTY OR LIABILITY. #
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# Visit our website for more info: https://msberends.gitab.io/AMR. #
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# ==================================================================== #
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#' Frequency table
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#'
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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{
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#' \item{Mean, using \code{\link[base]{mean}}}
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#' \item{Standard Deviation, using \code{\link[stats]{sd}}}
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#' \item{Coefficient of Variation (CV), the standard deviation divided by the mean}
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#' \item{Mean Absolute Deviation (MAD), using \code{\link[stats]{mad}}}
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#' \item{Tukey Five-Number Summaries (minimum, Q1, median, Q3, maximum), using \code{\link[stats]{fivenum}}}
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#' \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}
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#' \item{Coefficient of Quartile Variation (CQV, sometimes called coefficient of dispersion), calculated as \code{(Q3 - Q1) / (Q3 + Q1)} using the Tukey Five-Number Summaries}
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#' \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}}}
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#' \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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#' }
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#'
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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
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#' @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
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#' library(dplyr)
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#'
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#' # this all gives the same result:
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#' freq(septic_patients$hospital_id)
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#' freq(septic_patients[, "hospital_id"])
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#' septic_patients$hospital_id %>% freq()
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#' septic_patients[, "hospital_id"] %>% freq()
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#' 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 %>%
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#' filter(hospital_id == "A") %>%
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#' select(mo) %>%
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#' freq()
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#'
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#'
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#' # multiple selected variables will be pasted together
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#' septic_patients %>%
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#' left_join_microorganisms %>%
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#' freq(genus, species)
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#'
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#' # functions as quasiquotation are also supported
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#' septic_patients %>%
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#' freq(mo_genus(mo), mo_species(mo))
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#'
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#'
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#' # group a variable and analyse another
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#' septic_patients %>%
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#' group_by(hospital_id) %>%
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#' freq(gender)
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#'
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#'
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#' # get top 10 bugs of hospital A as a vector
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#' septic_patients %>%
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#' 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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#'
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#' # save frequency table to an object
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#' years <- septic_patients %>%
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#' 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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#'
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#' # save to an object with formatted percentages
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#' years <- format(years)
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#'
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#'
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#' # print a histogram of numeric values
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#' septic_patients %>%
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#' 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
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#' septic_patients %>%
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#' freq(age) %>%
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#' plot()
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#'
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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) %>%
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#' as.data.frame()
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#'
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#'
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#' # or transform (back) to a vector
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#' septic_patients %>%
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#' freq(age) %>%
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#' as.vector()
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#'
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#' identical(septic_patients %>%
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#' freq(age) %>%
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#' as.vector() %>%
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#' sort(),
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#' sort(septic_patients$age)) # TRUE
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#'
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#'
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#' # it also supports `table` objects
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#' table(septic_patients$gender,
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#' septic_patients$age) %>%
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#' freq(sep = " **sep** ")
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#'
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#'
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#' # only get selected columns
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#' septic_patients %>%
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#' freq(hospital_id) %>%
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#' select(item, percent)
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#'
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#' septic_patients %>%
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#' freq(hospital_id) %>%
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#' select(-count, -cum_count)
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#'
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#'
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#' # check differences between frequency tables
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#' diff(freq(septic_patients$trim),
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#' freq(septic_patients$trsu))
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frequency_tbl <- function(x,
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...,
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sort.count = TRUE,
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nmax = getOption("max.print.freq"),
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na.rm = TRUE,
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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 = " ",
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decimal.mark = getOption("OutDec"),
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big.mark = ifelse(decimal.mark != ",", ",", ".")) {
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mult.columns <- 0
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x.group = character(0)
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df <- NULL
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x.name <- NULL
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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)
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x <- as.data.frame(x, stringsAsFactors = FALSE)
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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)
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x.name <- "a matrix"
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cols <- colnames(x)
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if (all(cols %like% "V[0-9]")) {
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cols <- NULL
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}
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}
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if (any(class(x) == "data.frame")) {
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if (is.null(x.name)) {
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x.name <- deparse(substitute(x))
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}
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if (x.name %like% "(%>%)") {
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x.name <- x.name %>% strsplit("%>%", fixed = TRUE) %>% unlist() %>% .[1] %>% trimws()
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}
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if (x.name == ".") {
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x.name <- "a data.frame"
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} else {
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x.name <- paste0("`", x.name, "`")
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}
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x.name.dims <- x %>%
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dim() %>%
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format(decimal.mark = decimal.mark, big.mark = big.mark) %>%
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trimws() %>%
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paste(collapse = " x ")
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x.name <- paste0(x.name, " (", x.name.dims, ")")
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x.group <- group_vars(x)
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if (length(x.group) > 1) {
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x.group <- x.group[1L]
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warning("freq supports one grouping variable, only `", x.group, "` will be kept.", call. = FALSE)
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}
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user_exprs <- enquos(...)
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if (length(user_exprs) > 0) {
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new_list <- list(0)
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for (i in 1:length(user_exprs)) {
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new_list[[i]] <- eval_tidy(user_exprs[[i]], data = x)
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if (length(new_list[[i]]) == 1) {
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if (is.character(new_list[[i]]) & new_list[[i]] %in% colnames(x)) {
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# support septic_patients %>% freq("hospital_id")
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new_list[[i]] <- x %>% pull(new_list[[i]])
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}
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}
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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) {
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# is now character
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x <- new_list[[1]]
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df <- NULL
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} else {
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# create data frame
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df <- as.data.frame(new_list, col.names = cols, stringsAsFactors = FALSE)
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cols.names <- colnames(df)
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}
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} else {
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# complete data frame
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df <- x
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}
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# support grouping variables
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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)
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# if (droplevels == TRUE) {
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# x <- x %>% mutate_at(vars(x.group_cols), droplevels)
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# }
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suppressWarnings(
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df <- x %>%
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group_by_at(vars(x.group_cols)) %>%
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summarise(count = n())
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)
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if (na.rm == TRUE) {
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df <- df %>% filter_at(vars(x.group_cols), all_vars(!is.na(.)))
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}
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if (!missing(sort.count)) {
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if (sort.count == TRUE) {
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df <- df %>% arrange_at(c(x.group_cols, "count"), desc)
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}
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}
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df <- df %>%
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mutate(cum_count = cumsum(count))
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df.topleft <- df[1, 1]
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df <- df %>%
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ungroup() %>%
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# do not repeat group labels
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mutate_at(vars(x.group), funs(ifelse(lag(.) == ., "", .)))
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df[1, 1] <- df.topleft
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colnames(df)[1:2] <- c("group", "item")
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if (!is.null(levels(df$item)) & droplevels == TRUE) {
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# is factor
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df <- df %>% filter(count != 0)
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}
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} else {
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if (!is.null(df)) {
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# no groups, multiple values like: septic_patients %>% freq(mo, mo_genus(mo))
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x <- df
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df <- NULL
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}
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}
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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)
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# now this DF contains 3 columns: the 2 vars and a Freq column
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# paste the first 2 cols and repeat them Freq times:
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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 <- NULL
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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)
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} else if (ncol(x) < 10) {
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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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}
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}
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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 {
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NAs <- x[is.na(x)]
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}
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if (mult.columns > 0) {
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header_list <- list(columns = mult.columns)
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} else {
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header_list <- list(class = class(x),
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mode = mode(x))
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}
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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$levels <- levels(x)
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header_list$ordered <- is.ordered(x)
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# drop levels of non-existing factor values,
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# since dplyr >= 0.8.0 does not do this anymore in group_by
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if (droplevels == TRUE) {
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x <- droplevels(x)
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}
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}
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header_list$na_length <- length(NAs)
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header_list$unique <- n_distinct(x)
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if (NROW(x) > 0 & any(class(x) == "character")) {
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header_list$shortest <- x %>% base::nchar() %>% base::min(na.rm = TRUE)
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header_list$longest <- x %>% base::nchar() %>% base::max(na.rm = TRUE)
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}
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if (NROW(x) > 0 & any(class(x) == "mo")) {
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header_list$families <- x %>% mo_family() %>% n_distinct()
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header_list$genera <- x %>% mo_genus() %>% n_distinct()
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header_list$species <- x %>% mo_species() %>% n_distinct()
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}
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if (NROW(x) > 0 & any(class(x) == "difftime") & !is.hms(x)) {
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header_list$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)
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header_list$sd <- stats::sd(x, na.rm = TRUE)
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header_list$cv <- cv(x, na.rm = TRUE)
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header_list$mad <- stats::mad(x, na.rm = TRUE)
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Tukey_five <- stats::fivenum(x, na.rm = TRUE)
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header_list$fivenum <- Tukey_five
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header_list$IQR <- Tukey_five[4] - Tukey_five[2]
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header_list$cqv <- cqv(x, na.rm = TRUE)
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header_list$outliers_total <- length(boxplot.stats(x)$out)
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header_list$outliers_unique <- n_distinct(boxplot.stats(x)$out)
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}
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if (NROW(x) > 0 & any(class(x) == "rsi")) {
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header_list$count_S <- sum(x == "S", na.rm = TRUE)
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header_list$count_IR <- sum(x %in% c("I", "R"), 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()
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formatdates <- "%H:%M:%S"
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}
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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") {
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# hms
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header_list$earliest <- min(x, na.rm = TRUE)
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header_list$latest <- max(x, na.rm = TRUE)
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} else {
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# other date formats
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header_list$oldest <- min(x, na.rm = TRUE)
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header_list$newest <- max(x, na.rm = TRUE)
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}
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header_list$median <- median(x, na.rm = TRUE)
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header_list$date_format <- formatdates
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}
|
|
if (any(class(x) == "POSIXlt")) {
|
|
x <- x %>% format(formatdates)
|
|
}
|
|
|
|
nmax.set <- !missing(nmax)
|
|
if (!nmax.set & is.null(nmax) & is.null(base::getOption("max.print.freq", default = NULL))) {
|
|
# default for max print setting
|
|
nmax <- 15
|
|
} else if (is.null(nmax)) {
|
|
nmax <- length(x)
|
|
}
|
|
|
|
if (nmax %in% c(0, Inf, NA, NULL)) {
|
|
nmax <- length(x)
|
|
}
|
|
|
|
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")
|
|
|
|
if (is.null(df)) {
|
|
|
|
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())
|
|
)
|
|
|
|
# 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)
|
|
}
|
|
|
|
if (df$item %>% paste(collapse = ",") %like% "\033") {
|
|
# remove escape char
|
|
# see https://en.wikipedia.org/wiki/Escape_character#ASCII_escape_character
|
|
df <- df %>% mutate(item = item %>% gsub("\033", " ", ., fixed = TRUE))
|
|
}
|
|
|
|
if (quote == TRUE) {
|
|
df$item <- paste0('"', df$item, '"')
|
|
if (length(x.group) != 0) {
|
|
df$group <- paste0('"', df$group, '"')
|
|
}
|
|
}
|
|
|
|
df <- as.data.frame(df, stringsAsFactors = FALSE)
|
|
|
|
df$percent <- df$count / base::sum(df$count, na.rm = TRUE)
|
|
if (length(x.group) == 0) {
|
|
df$cum_count <- base::cumsum(df$count)
|
|
}
|
|
df$cum_percent <- df$cum_count / base::sum(df$count, na.rm = TRUE)
|
|
if (length(x.group) != 0) {
|
|
# sort columns
|
|
df <- df[, column_names_df]
|
|
}
|
|
|
|
if (markdown == TRUE) {
|
|
tbl_format <- "markdown"
|
|
} else {
|
|
tbl_format <- "pandoc"
|
|
}
|
|
|
|
if (!is.null(title)) {
|
|
title <- trimws(gsub("^Frequency table of", "", title[1L], ignore.case = TRUE))
|
|
}
|
|
|
|
# if (nmax.set == FALSE) {
|
|
# nmax <- nrow(df)
|
|
# }
|
|
|
|
structure(.Data = df,
|
|
class = c("frequency_tbl", class(df)),
|
|
header = header_list,
|
|
opt = list(title = title,
|
|
data = x.name,
|
|
vars = cols,
|
|
group_var = x.group,
|
|
header = header,
|
|
row_names = row.names,
|
|
column_names = column_names,
|
|
column_align = column_align,
|
|
decimal.mark = decimal.mark,
|
|
big.mark = big.mark,
|
|
tbl_format = tbl_format,
|
|
na = na,
|
|
digits = digits,
|
|
nmax = nmax,
|
|
nmax.set = nmax.set))
|
|
}
|
|
|
|
#' @rdname freq
|
|
#' @export
|
|
freq <- frequency_tbl
|
|
|
|
#' @importFrom crayon silver green red
|
|
#' @importFrom dplyr %>%
|
|
format_header <- function(x, markdown = FALSE, decimal.mark = ".", big.mark = ",", digits = 2) {
|
|
newline <-"\n"
|
|
if (markdown == TRUE) {
|
|
newline <- " \n"
|
|
# no colours in markdown
|
|
silver <- function(x) x
|
|
green <- function(x) x
|
|
red <- function(x) x
|
|
}
|
|
|
|
header <- header(x)
|
|
x_class <- header$class
|
|
has_length <- header$length > 0
|
|
|
|
# FORMATTING
|
|
# rsi
|
|
if (has_length == TRUE & any(x_class == "rsi")) {
|
|
if (header$count_S < header$count_IR) {
|
|
ratio <- paste0(green(1), ":", red(format(header$count_IR / header$count_S,
|
|
digits = 1, nsmall = 1, decimal.mark = decimal.mark, big.mark = big.mark)))
|
|
} else {
|
|
ratio <- paste0(green(format(header$count_S / header$count_IR,
|
|
digits = 1, nsmall = 1, decimal.mark = decimal.mark, big.mark = big.mark)),
|
|
":", red(1))
|
|
}
|
|
header$`%IR` <- paste((header$count_IR / header$length) %>% percent(force_zero = TRUE, round = digits, decimal.mark = decimal.mark),
|
|
paste0("(ratio ", ratio, ")"))
|
|
header <- header[!names(header) %in% c("count_S", "count_IR")]
|
|
}
|
|
# 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$columns)) {
|
|
if (markdown == TRUE) {
|
|
header$class <- paste0("`", header$class, "`")
|
|
}
|
|
if (!header$mode %in% header$class) {
|
|
if (markdown == TRUE) {
|
|
header$mode <- paste0("`", header$mode, "`")
|
|
}
|
|
header$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$levels)) {
|
|
if (markdown == TRUE) {
|
|
header$levels <- paste0("`", header$levels, "`")
|
|
}
|
|
if (header$ordered == TRUE) {
|
|
levels_text <- paste0(header$levels, collapse = " < ")
|
|
} else {
|
|
levels_text <- paste0(header$levels, collapse = ", ")
|
|
}
|
|
if (nchar(levels_text) > 70) {
|
|
# levels text wider than half the console
|
|
levels_text <- paste0(substr(levels_text, 1, 70 - 3), "...")
|
|
}
|
|
header$levels <- paste0(length(header$levels), ": ", levels_text)
|
|
header <- header[names(header) != "ordered"]
|
|
}
|
|
# length and NAs
|
|
if (has_length == TRUE) {
|
|
na_txt <- paste0(header$na_length %>% format(decimal.mark = decimal.mark, big.mark = big.mark), " = ",
|
|
(header$na_length / header$length) %>% percent(force_zero = TRUE, round = digits, decimal.mark = decimal.mark) %>%
|
|
sub("NaN", "0", ., fixed = TRUE))
|
|
if (!na_txt %like% "^0 =") {
|
|
na_txt <- red(na_txt)
|
|
} else {
|
|
na_txt <- green(na_txt)
|
|
}
|
|
na_txt <- paste0("(of which NA: ", na_txt, ")")
|
|
} else {
|
|
na_txt <- ""
|
|
}
|
|
header$length <- paste(format(header$length, decimal.mark = decimal.mark, big.mark = big.mark),
|
|
na_txt)
|
|
header <- header[names(header) != "na_length"]
|
|
|
|
# format all numeric values
|
|
header <- lapply(header, function(x) {
|
|
if (is.numeric(x)) {
|
|
if (any(x < 1000)) {
|
|
format(round2(x, digits = digits), decimal.mark = decimal.mark, big.mark = big.mark)
|
|
} else {
|
|
format(x, digits = digits, decimal.mark = decimal.mark, big.mark = big.mark)
|
|
}
|
|
} else {
|
|
x
|
|
}
|
|
})
|
|
|
|
# numeric values
|
|
if (has_length == TRUE & any(x_class %in% c("double", "integer", "numeric", "raw", "single"))) {
|
|
header$sd <- paste0(header$sd, " (CV: ", header$cv, ", MAD: ", header$mad, ")")
|
|
header$fivenum <- paste0(paste(trimws(header$fivenum), collapse = " | "), " (IQR: ", header$IQR, ", CQV: ", header$cqv, ")")
|
|
header$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)
|
|
}
|
|
|
|
#' @rdname freq
|
|
#' @export
|
|
#' @importFrom dplyr top_n pull
|
|
top_freq <- function(f, n) {
|
|
if (!"frequency_tbl" %in% class(f)) {
|
|
stop("`top_freq` can only be applied to frequency tables", call. = FALSE)
|
|
}
|
|
if (!is.numeric(n) | length(n) != 1L) {
|
|
stop("For `top_freq`, 'n' must be a number of length 1", call. = FALSE)
|
|
}
|
|
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
|
|
}
|
|
|
|
#' @rdname freq
|
|
#' @export
|
|
header <- function(f, property = NULL) {
|
|
if (!"frequency_tbl" %in% class(f)) {
|
|
stop("`header` can only be applied to frequency tables", call. = FALSE)
|
|
}
|
|
if (is.null(property)) {
|
|
attributes(f)$header
|
|
} else {
|
|
a <- attributes(f)$header
|
|
if (any(property %in% names(f))) {
|
|
a[names(a) %in% property]
|
|
}
|
|
}
|
|
}
|
|
|
|
#' @noRd
|
|
#' @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.")
|
|
}
|
|
|
|
cat("Differences between frequency tables")
|
|
if (identical(x, y)) {
|
|
cat("\n\nNo differences found.\n")
|
|
return(invisible())
|
|
}
|
|
|
|
x.attr <- attributes(x)$opt
|
|
|
|
# only keep item and count
|
|
x <- x[, 1:2]
|
|
y <- y[, 1:2]
|
|
|
|
x <- x %>%
|
|
full_join(y,
|
|
by = colnames(x)[1],
|
|
suffix = c(".x", ".y")) %>%
|
|
mutate(
|
|
diff = case_when(
|
|
is.na(count.y) ~ -count.x,
|
|
is.na(count.x) ~ count.y,
|
|
TRUE ~ count.y - count.x)) %>%
|
|
mutate(
|
|
diff.percent = percent(
|
|
diff / count.x,
|
|
force_zero = TRUE)) %>%
|
|
mutate(diff = ifelse(diff %like% "^-",
|
|
diff,
|
|
paste0("+", diff)),
|
|
diff.percent = ifelse(diff.percent %like% "^-",
|
|
diff.percent,
|
|
paste0("+", diff.percent)))
|
|
|
|
print(
|
|
knitr::kable(x,
|
|
format = x.attr$tbl_format,
|
|
col.names = c("Item", "Count #1", "Count #2", "Difference", "Diff. percent"),
|
|
align = paste0(x.attr$column_align[1], "rrrr"),
|
|
padding = 1)
|
|
)
|
|
}
|
|
|
|
#' @rdname freq
|
|
#' @exportMethod print.frequency_tbl
|
|
#' @importFrom knitr kable
|
|
#' @importFrom dplyr n_distinct
|
|
#' @importFrom crayon bold silver
|
|
#' @export
|
|
print.frequency_tbl <- function(x,
|
|
nmax = getOption("max.print.freq", default = 15),
|
|
markdown = !interactive(),
|
|
header = TRUE,
|
|
decimal.mark = getOption("OutDec"),
|
|
big.mark = ifelse(decimal.mark != ",", ",", "."),
|
|
...) {
|
|
|
|
opt <- attr(x, "opt")
|
|
opt$header_txt <- header(x)
|
|
|
|
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$tbl_format <- "pandoc"
|
|
}
|
|
}
|
|
|
|
if (length(opt$vars) == 0) {
|
|
opt$vars <- NULL
|
|
}
|
|
|
|
if (is.null(opt$title)) {
|
|
if (isTRUE(opt$data %like% "^a data.frame") & opt$tbl_format == "markdown") {
|
|
opt$data <- gsub("data.frame", "`data.frame`", opt$data, fixed = TRUE)
|
|
}
|
|
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$tbl_format == "pandoc") {
|
|
group_var <- silver(group_var)
|
|
}
|
|
title <- paste(title, group_var)
|
|
}
|
|
title <- trimws(title)
|
|
if (title == "") {
|
|
title <- "Frequency table"
|
|
} else {
|
|
title <- paste("Frequency table of", trimws(title))
|
|
}
|
|
} else {
|
|
title <- opt$title
|
|
}
|
|
|
|
if (!missing(nmax)) {
|
|
opt$nmax <- nmax
|
|
opt$nmax.set <- TRUE
|
|
}
|
|
if (opt$nmax %in% c(0, Inf, NA, NULL)) {
|
|
opt$nmax <- NROW(x)
|
|
opt$nmax.set <- FALSE
|
|
} else if (opt$nmax >= NROW(x)) {
|
|
opt$nmax.set <- FALSE
|
|
}
|
|
|
|
if (!missing(decimal.mark)) {
|
|
opt$decimal.mark <- decimal.mark
|
|
}
|
|
if (!missing(big.mark)) {
|
|
opt$big.mark <- big.mark
|
|
}
|
|
if (!missing(header)) {
|
|
opt$header <- header
|
|
}
|
|
|
|
# bold title
|
|
if (opt$tbl_format == "pandoc") {
|
|
title <- bold(title)
|
|
} else if (opt$tbl_format == "markdown") {
|
|
title <- paste0("\n\n**", title, "** ") # two space for newline
|
|
}
|
|
|
|
cat(title, "\n\n")
|
|
|
|
if (NROW(x) == 0) {
|
|
cat("No observations.\n")
|
|
if (opt$tbl_format == "markdown") {
|
|
cat("\n")
|
|
}
|
|
return(invisible())
|
|
}
|
|
|
|
if (opt$header == TRUE) {
|
|
if (!is.null(opt$header_txt)) {
|
|
if (is.null(opt$digits)) {
|
|
opt$digits <- 2
|
|
}
|
|
cat(format_header(x, digits = opt$digits, markdown = (opt$tbl_format == "markdown"),
|
|
decimal.mark = decimal.mark, big.mark = big.mark))
|
|
}
|
|
}
|
|
|
|
# save old NA setting for kable
|
|
opt.old <- options()$knitr.kable.NA
|
|
if (is.null(opt$na)) {
|
|
opt$na <- "<NA>"
|
|
}
|
|
if (opt$tbl_format == "markdown") {
|
|
# no HTML tags
|
|
opt$na <- gsub("<", "(", opt$na, fixed = TRUE)
|
|
opt$na <- gsub(">", ")", opt$na, fixed = TRUE)
|
|
}
|
|
options(knitr.kable.NA = opt$na)
|
|
|
|
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
|
|
|
|
if (nrow(x) > opt$nmax & opt$tbl_format != "markdown") {
|
|
|
|
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 = "")
|
|
} else {
|
|
footer <- '[ reached getOption("max.print.freq")'
|
|
}
|
|
footer <- paste(footer,
|
|
" -- 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 = "")
|
|
if (opt$tbl_format == "pandoc") {
|
|
footer <- silver(footer) # only silver in regular printing
|
|
}
|
|
} else if (opt$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
|
|
}
|
|
} else {
|
|
footer <- NULL
|
|
}
|
|
|
|
if ("item" %in% colnames(x)) {
|
|
if (any(class(x$item) %in% c("double", "integer", "numeric", "raw", "single"))) {
|
|
x$item <- format(x$item, decimal.mark = opt$decimal.mark, big.mark = opt$big.mark)
|
|
}
|
|
} else {
|
|
opt$column_names <- opt$column_names[!opt$column_names == "Item"]
|
|
}
|
|
if ("count" %in% colnames(x)) {
|
|
if (all(x$count == 1)) {
|
|
warning("All observations are unique.", call. = FALSE)
|
|
}
|
|
x$count <- format(x$count, decimal.mark = opt$decimal.mark, big.mark = opt$big.mark)
|
|
} else {
|
|
opt$column_names <- opt$column_names[!opt$column_names == "Count"]
|
|
}
|
|
if ("percent" %in% colnames(x)) {
|
|
x$percent <- percent(x$percent, force_zero = TRUE, decimal.mark = opt$decimal.mark)
|
|
} else {
|
|
opt$column_names <- opt$column_names[!opt$column_names == "Percent"]
|
|
}
|
|
if ("cum_count" %in% colnames(x)) {
|
|
x$cum_count <- format(x$cum_count, decimal.mark = opt$decimal.mark, big.mark = opt$big.mark)
|
|
} else {
|
|
opt$column_names <- opt$column_names[!opt$column_names == "Cum. Count"]
|
|
}
|
|
if ("cum_percent" %in% colnames(x)) {
|
|
x$cum_percent <- percent(x$cum_percent, force_zero = TRUE, decimal.mark = opt$decimal.mark)
|
|
} else {
|
|
opt$column_names <- opt$column_names[!opt$column_names == "Cum. Percent"]
|
|
}
|
|
|
|
if (opt$tbl_format == "markdown") {
|
|
cat("\n")
|
|
}
|
|
|
|
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)
|
|
}
|
|
|
|
if (opt$tbl_format == "markdown") {
|
|
cat("\n\n")
|
|
} else {
|
|
cat("\n")
|
|
}
|
|
|
|
# reset old kable setting
|
|
options(knitr.kable.NA = opt.old)
|
|
return(invisible())
|
|
|
|
}
|
|
|
|
#' @noRd
|
|
#' @exportMethod as.data.frame.frequency_tbl
|
|
#' @export
|
|
as.data.frame.frequency_tbl <- function(x, ...) {
|
|
attr(x, "package") <- NULL
|
|
attr(x, "opt") <- NULL
|
|
as.data.frame.data.frame(x, ...)
|
|
}
|
|
|
|
#' @exportMethod select.frequency_tbl
|
|
#' @export
|
|
#' @importFrom dplyr select
|
|
#' @noRd
|
|
select.frequency_tbl <- function(.data, ...) {
|
|
select(as.data.frame(.data), ...)
|
|
}
|
|
|
|
#' @noRd
|
|
#' @exportMethod as_tibble.frequency_tbl
|
|
#' @export
|
|
#' @importFrom dplyr as_tibble
|
|
as_tibble.frequency_tbl <- function(x, validate = TRUE, ..., rownames = NA) {
|
|
attr(x, "package") <- NULL
|
|
attr(x, "opt") <- NULL
|
|
as_tibble(x = as.data.frame(x), validate = validate, ..., rownames = rownames)
|
|
}
|
|
|
|
#' @noRd
|
|
#' @exportMethod hist.frequency_tbl
|
|
#' @export
|
|
#' @importFrom graphics hist
|
|
hist.frequency_tbl <- function(x, breaks = "Sturges", main = NULL, xlab = NULL, ...) {
|
|
opt <- attr(x, "opt")
|
|
if (!class(x$item) %in% c("numeric", "double", "integer", "Date")) {
|
|
stop("`x` must be numeric or Date.", call. = FALSE)
|
|
}
|
|
if (!is.null(opt$vars)) {
|
|
title <- opt$vars
|
|
} else if (!is.null(opt$data)) {
|
|
title <- opt$data
|
|
} else {
|
|
title <- "frequency table"
|
|
}
|
|
if (class(x$item) == "Date") {
|
|
x <- as.Date(as.vector(x), origin = "1970-01-01")
|
|
} else {
|
|
x <- as.vector(x)
|
|
}
|
|
if (is.null(main)) {
|
|
main <- paste("Histogram of", title)
|
|
}
|
|
if (is.null(xlab)) {
|
|
xlab <- title
|
|
}
|
|
hist(x, main = main, xlab = xlab, breaks = breaks, ...)
|
|
}
|
|
|
|
#' @noRd
|
|
#' @exportMethod plot.frequency_tbl
|
|
#' @export
|
|
plot.frequency_tbl <- function(x, y, ...) {
|
|
opt <- attr(x, "opt")
|
|
if (!is.null(opt$vars)) {
|
|
title <- opt$vars
|
|
} else {
|
|
title <- ""
|
|
}
|
|
plot(x = x$item, y = x$count, ylab = "Count", xlab = title, ...)
|
|
}
|
|
|
|
#' @noRd
|
|
#' @exportMethod as.vector.frequency_tbl
|
|
#' @export
|
|
as.vector.frequency_tbl <- function(x, mode = "any") {
|
|
as.vector(rep(x$item, x$count), mode = mode)
|
|
}
|
|
|
|
#' @noRd
|
|
#' @exportMethod format.frequency_tbl
|
|
#' @export
|
|
format.frequency_tbl <- function(x, digits = 1, ...) {
|
|
opt <- attr(x, "opt")
|
|
if (opt$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, ...)
|
|
}
|