mirror of https://github.com/msberends/AMR.git
param header for freq
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parent
86b03577a7
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3
NEWS.md
3
NEWS.md
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@ -19,7 +19,8 @@
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* Using `portion_*` functions now throws a warning when total available isolate is below parameter `minimum`
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* Functions `as.mo`, `as.rsi` and `as.mic` will not set package name as attribute anymore
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* Data set `septic_patients` is now a `data.frame`, not a tibble anymore
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* Check for `hms::is.hms` in frequency tables
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* Check for `hms::is.hms` in frequency tables (`freq()`)
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* New parameter `header` for frequency tables to turn them off (default when `markdown = TRUE`)
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* Removed diacritics from all authors (columns `microorganisms$ref` and `microorganisms.old$ref`) to comply with CRAN policy to only allow ASCII characters
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* Fix for `mo_property` not working properly
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* Fix for `EUCAST_rules` where some Streptococci would become ceftazidime R in EUCAST rule 4.5
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74
R/freq.R
74
R/freq.R
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@ -23,17 +23,18 @@
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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
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#' @param sort.count sort on count, i.e. frequencies. This will be \code{TRUE} at default for everything except for factors.
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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 will always print the amount of \code{NA}s.
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#' @param na.rm a logical value indicating whether \code{NA} values should be removed from the frequency table. The header_txt 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 print table in markdown format (this forces \code{nmax = NA})
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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 digits how many significant digits are to be used for numeric values in the header_txt (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 sep a character string to separate the terms when selecting multiple columns
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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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#' @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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#' For numeric values of any class, these additional values will all be calculated with \code{na.rm = TRUE} and shown into the header_txt:
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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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@ -45,7 +46,7 @@
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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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#' For dates and times of any class, these additional values will be calculated with \code{na.rm = TRUE} and shown into the header_txt:
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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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@ -156,6 +157,7 @@ frequency_tbl <- function(x,
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markdown = FALSE,
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digits = 2,
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quote = FALSE,
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header = !markdown,
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sep = " ") {
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mult.columns <- 0
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@ -309,7 +311,7 @@ frequency_tbl <- function(x,
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sort.count <- FALSE
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}
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header <- character(0)
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header_txt <- character(0)
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markdown_line <- ''
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if (markdown == TRUE) {
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@ -318,11 +320,11 @@ frequency_tbl <- function(x,
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x_align <- 'l'
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if (mult.columns > 0) {
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header <- header %>% paste0(markdown_line, 'Columns: ', mult.columns)
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header_txt <- header_txt %>% paste0(markdown_line, 'Columns: ', mult.columns)
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} else {
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header <- header %>% paste0(markdown_line, 'Class: ', class(x) %>% rev() %>% paste(collapse = " > "))
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header_txt <- header_txt %>% paste0(markdown_line, 'Class: ', class(x) %>% rev() %>% paste(collapse = " > "))
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if (!mode(x) %in% class(x)) {
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header <- header %>% paste0(silver(paste0(" (", mode(x), ")")))
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header_txt <- header_txt %>% paste0(silver(paste0(" (", mode(x), ")")))
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}
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}
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@ -334,53 +336,53 @@ frequency_tbl <- function(x,
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}
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}
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header <- header %>% paste0(markdown_line, '\nLength: ', (NAs %>% length() + x %>% length()) %>% format(),
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header_txt <- header_txt %>% paste0(markdown_line, '\nLength: ', (NAs %>% length() + x %>% length()) %>% format(),
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' (of which NA: ', NAs %>% length() %>% format() %>% NAs_to_red(),
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' = ', (NAs %>% length() / (NAs %>% length() + x %>% length())) %>%
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percent(force_zero = TRUE, round = digits) %>%
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sub('NaN', '0', ., fixed = TRUE) %>%
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NAs_to_red(), ')')
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header <- header %>% paste0(markdown_line, '\nUnique: ', x %>% n_distinct() %>% format())
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header_txt <- header_txt %>% paste0(markdown_line, '\nUnique: ', x %>% n_distinct() %>% format())
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if (NROW(x) > 0 & any(class(x) == "character")) {
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header <- header %>% paste0('\n')
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header <- header %>% paste0(markdown_line, '\nShortest: ', x %>% base::nchar() %>% base::min(na.rm = TRUE))
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header <- header %>% paste0(markdown_line, '\nLongest: ', x %>% base::nchar() %>% base::max(na.rm = TRUE))
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header_txt <- header_txt %>% paste0('\n')
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header_txt <- header_txt %>% paste0(markdown_line, '\nShortest: ', x %>% base::nchar() %>% base::min(na.rm = TRUE))
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header_txt <- header_txt %>% paste0(markdown_line, '\nLongest: ', x %>% base::nchar() %>% base::max(na.rm = TRUE))
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}
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if (NROW(x) > 0 & any(class(x) == "difftime")) {
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header <- header %>% paste0('\n')
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header <- header %>% paste(markdown_line, '\nUnits: ', attributes(x)$units)
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header_txt <- header_txt %>% paste0('\n')
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header_txt <- header_txt %>% paste(markdown_line, '\nUnits: ', attributes(x)$units)
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x <- as.double(x)
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# after this, the numeric header continues
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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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Tukey_five <- stats::fivenum(x, na.rm = TRUE)
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x_align <- 'r'
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header <- header %>% paste0('\n')
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header <- header %>% paste(markdown_line, '\nMean: ', x %>% base::mean(na.rm = TRUE) %>% format(digits = digits))
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header <- header %>% paste0(markdown_line, '\nStd. dev.: ', x %>% stats::sd(na.rm = TRUE) %>% format(digits = digits),
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header_txt <- header_txt %>% paste0('\n')
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header_txt <- header_txt %>% paste(markdown_line, '\nMean: ', x %>% base::mean(na.rm = TRUE) %>% format(digits = digits))
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header_txt <- header_txt %>% paste0(markdown_line, '\nStd. dev.: ', x %>% stats::sd(na.rm = TRUE) %>% format(digits = digits),
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' (CV: ', x %>% cv(na.rm = TRUE) %>% format(digits = digits),
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', MAD: ', x %>% stats::mad(na.rm = TRUE) %>% format(digits = digits), ')')
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header <- header %>% paste0(markdown_line, '\nFive-Num: ', Tukey_five %>% format(digits = digits) %>% trimws() %>% paste(collapse = ' | '),
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header_txt <- header_txt %>% paste0(markdown_line, '\nFive-Num: ', Tukey_five %>% format(digits = digits) %>% trimws() %>% paste(collapse = ' | '),
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' (IQR: ', (Tukey_five[4] - Tukey_five[2]) %>% format(digits = digits),
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', CQV: ', x %>% cqv(na.rm = TRUE) %>% format(digits = digits), ')')
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outlier_length <- length(boxplot.stats(x)$out)
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header <- header %>% paste0(markdown_line, '\nOutliers: ', outlier_length)
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header_txt <- header_txt %>% paste0(markdown_line, '\nOutliers: ', outlier_length)
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if (outlier_length > 0) {
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header <- header %>% paste0(' (unique count: ', boxplot.stats(x)$out %>% n_distinct(), ')')
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header_txt <- header_txt %>% paste0(' (unique count: ', boxplot.stats(x)$out %>% n_distinct(), ')')
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}
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}
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if (NROW(x) > 0 & any(class(x) == "rsi")) {
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header <- header %>% paste0('\n')
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header_txt <- header_txt %>% paste0('\n')
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cnt_S <- sum(x == "S")
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cnt_I <- sum(x == "I")
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cnt_R <- sum(x == "R")
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header <- header %>% paste(markdown_line, '\n%IR: ',
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header_txt <- header_txt %>% paste(markdown_line, '\n%IR: ',
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((cnt_I + cnt_R) / sum(!is.na(x))) %>% percent(force_zero = TRUE, round = digits))
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header <- header %>% paste0(markdown_line, '\nRatio SIR: 1.0 : ',
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header_txt <- header_txt %>% paste0(markdown_line, '\nRatio SIR: 1.0 : ',
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(cnt_I / cnt_S) %>% format(digits = 1, nsmall = 1), " : ",
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(cnt_R / cnt_S) %>% format(digits = 1, nsmall = 1))
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}
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@ -391,7 +393,7 @@ frequency_tbl <- function(x,
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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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header <- header %>% paste0('\n')
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header_txt <- header_txt %>% paste0('\n')
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mindate <- x %>% min(na.rm = TRUE)
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maxdate <- x %>% max(na.rm = TRUE)
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maxdate_days <- difftime(maxdate, mindate, units = 'auto') %>% as.double()
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@ -400,16 +402,16 @@ frequency_tbl <- function(x,
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if (formatdates == "%H:%M:%S") {
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# hms
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header <- header %>% paste0(markdown_line, '\nEarliest: ', mindate %>% format(formatdates) %>% trimws())
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header <- header %>% paste0(markdown_line, '\nLatest: ', maxdate %>% format(formatdates) %>% trimws(),
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header_txt <- header_txt %>% paste0(markdown_line, '\nEarliest: ', mindate %>% format(formatdates) %>% trimws())
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header_txt <- header_txt %>% paste0(markdown_line, '\nLatest: ', maxdate %>% format(formatdates) %>% trimws(),
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' (+', difftime(maxdate, mindate, units = 'mins') %>% as.double() %>% format(digits = digits), ' min.)')
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} else {
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# other date formats
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header <- header %>% paste0(markdown_line, '\nOldest: ', mindate %>% format(formatdates) %>% trimws())
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header <- header %>% paste0(markdown_line, '\nNewest: ', maxdate %>% format(formatdates) %>% trimws(),
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header_txt <- header_txt %>% paste0(markdown_line, '\nOldest: ', mindate %>% format(formatdates) %>% trimws())
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header_txt <- header_txt %>% paste0(markdown_line, '\nNewest: ', maxdate %>% format(formatdates) %>% trimws(),
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' (+', difftime(maxdate, mindate, units = 'auto') %>% as.double() %>% format(digits = digits), ')')
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}
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header <- header %>% paste0(markdown_line, '\nMedian: ', mediandate %>% format(formatdates) %>% trimws(),
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header_txt <- header_txt %>% paste0(markdown_line, '\nMedian: ', mediandate %>% format(formatdates) %>% trimws(),
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' (~', percent(median_days / maxdate_days, round = 0), ')')
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}
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if (any(class(x) == 'POSIXlt')) {
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@ -493,6 +495,7 @@ frequency_tbl <- function(x,
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attr(df, 'opt') <- list(data = x.name,
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vars = cols,
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header = header,
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header_txt = header_txt,
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row_names = row.names,
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column_names = column_names,
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column_align = column_align,
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@ -621,10 +624,11 @@ print.frequency_tbl <- function(x, nmax = getOption("max.print.freq", default =
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title <- bold(title) # only bold in regular printing
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}
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cat(title, "\n")
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if (!is.null(opt$header)) {
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cat(opt$header)
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if (opt$header == TRUE) {
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cat(title, "\n")
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if (!is.null(opt$header_txt)) {
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cat(opt$header_txt)
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}
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}
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if (NROW(x) == 0) {
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15
man/freq.Rd
15
man/freq.Rd
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@ -9,11 +9,12 @@
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\usage{
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frequency_tbl(x, ..., sort.count = TRUE,
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nmax = getOption("max.print.freq"), na.rm = TRUE, row.names = TRUE,
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markdown = FALSE, digits = 2, quote = FALSE, sep = " ")
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markdown = FALSE, digits = 2, quote = FALSE, header = !markdown,
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sep = " ")
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freq(x, ..., sort.count = TRUE, nmax = getOption("max.print.freq"),
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na.rm = TRUE, row.names = TRUE, markdown = FALSE, digits = 2,
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quote = FALSE, sep = " ")
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quote = FALSE, header = !markdown, sep = " ")
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top_freq(f, n)
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@ -29,16 +30,18 @@ top_freq(f, n)
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\item{nmax}{number of row to print. The default, \code{15}, uses \code{\link{getOption}("max.print.freq")}. Use \code{nmax = 0}, \code{nmax = Inf}, \code{nmax = NULL} or \code{nmax = NA} to print all rows.}
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\item{na.rm}{a logical value indicating whether \code{NA} values should be removed from the frequency table. The header will always print the amount of \code{NA}s.}
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\item{na.rm}{a logical value indicating whether \code{NA} values should be removed from the frequency table. The header_txt will always print the amount of \code{NA}s.}
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\item{row.names}{a logical value indicating whether row indices should be printed as \code{1:nrow(x)}}
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\item{markdown}{print table in markdown format (this forces \code{nmax = NA})}
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\item{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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\item{digits}{how many significant digits are to be used for numeric values in the header_txt (not for the items themselves, that depends on \code{\link{getOption}("digits")})}
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\item{quote}{a logical value indicating whether or not strings should be printed with surrounding quotes}
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\item{header}{a logical value indicating whether an informative header should be printed}
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\item{sep}{a character string to separate the terms when selecting multiple columns}
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\item{f}{a frequency table}
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@ -54,7 +57,7 @@ Create a frequency table of a vector with items or a data frame. Supports quasiq
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\details{
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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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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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For numeric values of any class, these additional values will all be calculated with \code{na.rm = TRUE} and shown into the header_txt:
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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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@ -66,7 +69,7 @@ For numeric values of any class, these additional values will all be calculated
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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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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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For dates and times of any class, these additional values will be calculated with \code{na.rm = TRUE} and shown into the header_txt:
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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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