diff --git a/NEWS.md b/NEWS.md index 567fb82e..7a0ba270 100755 --- a/NEWS.md +++ b/NEWS.md @@ -19,7 +19,8 @@ * Using `portion_*` functions now throws a warning when total available isolate is below parameter `minimum` * Functions `as.mo`, `as.rsi` and `as.mic` will not set package name as attribute anymore * Data set `septic_patients` is now a `data.frame`, not a tibble anymore -* Check for `hms::is.hms` in frequency tables +* Check for `hms::is.hms` in frequency tables (`freq()`) +* New parameter `header` for frequency tables to turn them off (default when `markdown = TRUE`) * Removed diacritics from all authors (columns `microorganisms$ref` and `microorganisms.old$ref`) to comply with CRAN policy to only allow ASCII characters * Fix for `mo_property` not working properly * Fix for `EUCAST_rules` where some Streptococci would become ceftazidime R in EUCAST rule 4.5 diff --git a/R/freq.R b/R/freq.R index 13dc9225..968135da 100755 --- a/R/freq.R +++ b/R/freq.R @@ -23,17 +23,18 @@ #' @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 #' @param sort.count sort on count, i.e. frequencies. This will be \code{TRUE} at default for everything except for factors. #' @param nmax number of row to print. The default, \code{15}, uses \code{\link{getOption}("max.print.freq")}. Use \code{nmax = 0}, \code{nmax = Inf}, \code{nmax = NULL} or \code{nmax = NA} to print all rows. -#' @param na.rm a logical value indicating whether \code{NA} values should be removed from the frequency table. The header will always print the amount of \code{NA}s. +#' @param 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. #' @param row.names a logical value indicating whether row indices should be printed as \code{1:nrow(x)} #' @param markdown print table in markdown format (this forces \code{nmax = NA}) -#' @param digits how many significant digits are to be used for numeric values in the header (not for the items themselves, that depends on \code{\link{getOption}("digits")}) +#' @param 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")}) #' @param quote a logical value indicating whether or not strings should be printed with surrounding quotes +#' @param header a logical value indicating whether an informative header should be printed #' @param sep a character string to separate the terms when selecting multiple columns #' @param f a frequency table #' @param n number of top \emph{n} items to return, use -n for the bottom \emph{n} items. It will include more than \code{n} rows if there are ties. #' @details Frequency tables (or frequency distributions) are summaries of the distribution of values in a sample. With the `freq` function, you can create univariate frequency tables. Multiple variables will be pasted into one variable, so it forces a univariate distribution. This package also has a vignette available to explain the use of this function further, run \code{browseVignettes("AMR")} to read it. #' -#' For numeric values of any class, these additional values will all be calculated with \code{na.rm = TRUE} and shown into the header: +#' For numeric values of any class, these additional values will all be calculated with \code{na.rm = TRUE} and shown into the header_txt: #' \itemize{ #' \item{Mean, using \code{\link[base]{mean}}} #' \item{Standard Deviation, using \code{\link[stats]{sd}}} @@ -45,7 +46,7 @@ #' \item{Outliers (total count and unique count), using \code{\link[grDevices]{boxplot.stats}}} #' } #' -#' For dates and times of any class, these additional values will be calculated with \code{na.rm = TRUE} and shown into the header: +#' For dates and times of any class, these additional values will be calculated with \code{na.rm = TRUE} and shown into the header_txt: #' \itemize{ #' \item{Oldest, using \code{\link{min}}} #' \item{Newest, using \code{\link{max}}, with difference between newest and oldest} @@ -156,6 +157,7 @@ frequency_tbl <- function(x, markdown = FALSE, digits = 2, quote = FALSE, + header = !markdown, sep = " ") { mult.columns <- 0 @@ -309,7 +311,7 @@ frequency_tbl <- function(x, sort.count <- FALSE } - header <- character(0) + header_txt <- character(0) markdown_line <- '' if (markdown == TRUE) { @@ -318,11 +320,11 @@ frequency_tbl <- function(x, x_align <- 'l' if (mult.columns > 0) { - header <- header %>% paste0(markdown_line, 'Columns: ', mult.columns) + header_txt <- header_txt %>% paste0(markdown_line, 'Columns: ', mult.columns) } else { - header <- header %>% paste0(markdown_line, 'Class: ', class(x) %>% rev() %>% paste(collapse = " > ")) + header_txt <- header_txt %>% paste0(markdown_line, 'Class: ', class(x) %>% rev() %>% paste(collapse = " > ")) if (!mode(x) %in% class(x)) { - header <- header %>% paste0(silver(paste0(" (", mode(x), ")"))) + header_txt <- header_txt %>% paste0(silver(paste0(" (", mode(x), ")"))) } } @@ -334,53 +336,53 @@ frequency_tbl <- function(x, } } - header <- header %>% paste0(markdown_line, '\nLength: ', (NAs %>% length() + x %>% length()) %>% format(), + header_txt <- header_txt %>% paste0(markdown_line, '\nLength: ', (NAs %>% length() + x %>% length()) %>% format(), ' (of which NA: ', NAs %>% length() %>% format() %>% NAs_to_red(), ' = ', (NAs %>% length() / (NAs %>% length() + x %>% length())) %>% percent(force_zero = TRUE, round = digits) %>% sub('NaN', '0', ., fixed = TRUE) %>% NAs_to_red(), ')') - header <- header %>% paste0(markdown_line, '\nUnique: ', x %>% n_distinct() %>% format()) + header_txt <- header_txt %>% paste0(markdown_line, '\nUnique: ', x %>% n_distinct() %>% format()) if (NROW(x) > 0 & any(class(x) == "character")) { - header <- header %>% paste0('\n') - header <- header %>% paste0(markdown_line, '\nShortest: ', x %>% base::nchar() %>% base::min(na.rm = TRUE)) - header <- header %>% paste0(markdown_line, '\nLongest: ', x %>% base::nchar() %>% base::max(na.rm = TRUE)) + header_txt <- header_txt %>% paste0('\n') + header_txt <- header_txt %>% paste0(markdown_line, '\nShortest: ', x %>% base::nchar() %>% base::min(na.rm = TRUE)) + header_txt <- header_txt %>% paste0(markdown_line, '\nLongest: ', x %>% base::nchar() %>% base::max(na.rm = TRUE)) } if (NROW(x) > 0 & any(class(x) == "difftime")) { - header <- header %>% paste0('\n') - header <- header %>% paste(markdown_line, '\nUnits: ', attributes(x)$units) + header_txt <- header_txt %>% paste0('\n') + header_txt <- header_txt %>% paste(markdown_line, '\nUnits: ', attributes(x)$units) x <- as.double(x) - # after this, the numeric header continues + # after this, the numeric header_txt continues } if (NROW(x) > 0 & any(class(x) %in% c('double', 'integer', 'numeric', 'raw', 'single'))) { # right align number Tukey_five <- stats::fivenum(x, na.rm = TRUE) x_align <- 'r' - header <- header %>% paste0('\n') - header <- header %>% paste(markdown_line, '\nMean: ', x %>% base::mean(na.rm = TRUE) %>% format(digits = digits)) - header <- header %>% paste0(markdown_line, '\nStd. dev.: ', x %>% stats::sd(na.rm = TRUE) %>% format(digits = digits), + header_txt <- header_txt %>% paste0('\n') + header_txt <- header_txt %>% paste(markdown_line, '\nMean: ', x %>% base::mean(na.rm = TRUE) %>% format(digits = digits)) + header_txt <- header_txt %>% paste0(markdown_line, '\nStd. dev.: ', x %>% stats::sd(na.rm = TRUE) %>% format(digits = digits), ' (CV: ', x %>% cv(na.rm = TRUE) %>% format(digits = digits), ', MAD: ', x %>% stats::mad(na.rm = TRUE) %>% format(digits = digits), ')') - header <- header %>% paste0(markdown_line, '\nFive-Num: ', Tukey_five %>% format(digits = digits) %>% trimws() %>% paste(collapse = ' | '), + header_txt <- header_txt %>% paste0(markdown_line, '\nFive-Num: ', Tukey_five %>% format(digits = digits) %>% trimws() %>% paste(collapse = ' | '), ' (IQR: ', (Tukey_five[4] - Tukey_five[2]) %>% format(digits = digits), ', CQV: ', x %>% cqv(na.rm = TRUE) %>% format(digits = digits), ')') outlier_length <- length(boxplot.stats(x)$out) - header <- header %>% paste0(markdown_line, '\nOutliers: ', outlier_length) + header_txt <- header_txt %>% paste0(markdown_line, '\nOutliers: ', outlier_length) if (outlier_length > 0) { - header <- header %>% paste0(' (unique count: ', boxplot.stats(x)$out %>% n_distinct(), ')') + header_txt <- header_txt %>% paste0(' (unique count: ', boxplot.stats(x)$out %>% n_distinct(), ')') } } if (NROW(x) > 0 & any(class(x) == "rsi")) { - header <- header %>% paste0('\n') + header_txt <- header_txt %>% paste0('\n') cnt_S <- sum(x == "S") cnt_I <- sum(x == "I") cnt_R <- sum(x == "R") - header <- header %>% paste(markdown_line, '\n%IR: ', + header_txt <- header_txt %>% paste(markdown_line, '\n%IR: ', ((cnt_I + cnt_R) / sum(!is.na(x))) %>% percent(force_zero = TRUE, round = digits)) - header <- header %>% paste0(markdown_line, '\nRatio SIR: 1.0 : ', + header_txt <- header_txt %>% paste0(markdown_line, '\nRatio SIR: 1.0 : ', (cnt_I / cnt_S) %>% format(digits = 1, nsmall = 1), " : ", (cnt_R / cnt_S) %>% format(digits = 1, nsmall = 1)) } @@ -391,7 +393,7 @@ frequency_tbl <- function(x, formatdates <- "%H:%M:%S" } if (NROW(x) > 0 & any(class(x) %in% c('Date', 'POSIXct', 'POSIXlt'))) { - header <- header %>% paste0('\n') + header_txt <- header_txt %>% paste0('\n') mindate <- x %>% min(na.rm = TRUE) maxdate <- x %>% max(na.rm = TRUE) maxdate_days <- difftime(maxdate, mindate, units = 'auto') %>% as.double() @@ -400,16 +402,16 @@ frequency_tbl <- function(x, if (formatdates == "%H:%M:%S") { # hms - header <- header %>% paste0(markdown_line, '\nEarliest: ', mindate %>% format(formatdates) %>% trimws()) - header <- header %>% paste0(markdown_line, '\nLatest: ', maxdate %>% format(formatdates) %>% trimws(), + header_txt <- header_txt %>% paste0(markdown_line, '\nEarliest: ', mindate %>% format(formatdates) %>% trimws()) + header_txt <- header_txt %>% paste0(markdown_line, '\nLatest: ', maxdate %>% format(formatdates) %>% trimws(), ' (+', difftime(maxdate, mindate, units = 'mins') %>% as.double() %>% format(digits = digits), ' min.)') } else { # other date formats - header <- header %>% paste0(markdown_line, '\nOldest: ', mindate %>% format(formatdates) %>% trimws()) - header <- header %>% paste0(markdown_line, '\nNewest: ', maxdate %>% format(formatdates) %>% trimws(), + header_txt <- header_txt %>% paste0(markdown_line, '\nOldest: ', mindate %>% format(formatdates) %>% trimws()) + header_txt <- header_txt %>% paste0(markdown_line, '\nNewest: ', maxdate %>% format(formatdates) %>% trimws(), ' (+', difftime(maxdate, mindate, units = 'auto') %>% as.double() %>% format(digits = digits), ')') } - header <- header %>% paste0(markdown_line, '\nMedian: ', mediandate %>% format(formatdates) %>% trimws(), + header_txt <- header_txt %>% paste0(markdown_line, '\nMedian: ', mediandate %>% format(formatdates) %>% trimws(), ' (~', percent(median_days / maxdate_days, round = 0), ')') } if (any(class(x) == 'POSIXlt')) { @@ -493,6 +495,7 @@ frequency_tbl <- function(x, attr(df, 'opt') <- list(data = x.name, vars = cols, header = header, + header_txt = header_txt, row_names = row.names, column_names = column_names, column_align = column_align, @@ -621,10 +624,11 @@ print.frequency_tbl <- function(x, nmax = getOption("max.print.freq", default = title <- bold(title) # only bold in regular printing } - cat(title, "\n") - - if (!is.null(opt$header)) { - cat(opt$header) + if (opt$header == TRUE) { + cat(title, "\n") + if (!is.null(opt$header_txt)) { + cat(opt$header_txt) + } } if (NROW(x) == 0) { diff --git a/man/freq.Rd b/man/freq.Rd index 495c40af..f69f2575 100755 --- a/man/freq.Rd +++ b/man/freq.Rd @@ -9,11 +9,12 @@ \usage{ frequency_tbl(x, ..., sort.count = TRUE, nmax = getOption("max.print.freq"), na.rm = TRUE, row.names = TRUE, - markdown = FALSE, digits = 2, quote = FALSE, sep = " ") + markdown = FALSE, digits = 2, quote = FALSE, header = !markdown, + sep = " ") freq(x, ..., sort.count = TRUE, nmax = getOption("max.print.freq"), na.rm = TRUE, row.names = TRUE, markdown = FALSE, digits = 2, - quote = FALSE, sep = " ") + quote = FALSE, header = !markdown, sep = " ") top_freq(f, n) @@ -29,16 +30,18 @@ top_freq(f, n) \item{nmax}{number of row to print. The default, \code{15}, uses \code{\link{getOption}("max.print.freq")}. Use \code{nmax = 0}, \code{nmax = Inf}, \code{nmax = NULL} or \code{nmax = NA} to print all rows.} -\item{na.rm}{a logical value indicating whether \code{NA} values should be removed from the frequency table. The header will always print the amount of \code{NA}s.} +\item{na.rm}{a logical value indicating whether \code{NA} values should be removed from the frequency table. The header_txt will always print the amount of \code{NA}s.} \item{row.names}{a logical value indicating whether row indices should be printed as \code{1:nrow(x)}} \item{markdown}{print table in markdown format (this forces \code{nmax = NA})} -\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")})} +\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")})} \item{quote}{a logical value indicating whether or not strings should be printed with surrounding quotes} +\item{header}{a logical value indicating whether an informative header should be printed} + \item{sep}{a character string to separate the terms when selecting multiple columns} \item{f}{a frequency table} @@ -54,7 +57,7 @@ Create a frequency table of a vector with items or a data frame. Supports quasiq \details{ Frequency tables (or frequency distributions) are summaries of the distribution of values in a sample. With the `freq` function, you can create univariate frequency tables. Multiple variables will be pasted into one variable, so it forces a univariate distribution. This package also has a vignette available to explain the use of this function further, run \code{browseVignettes("AMR")} to read it. -For numeric values of any class, these additional values will all be calculated with \code{na.rm = TRUE} and shown into the header: +For numeric values of any class, these additional values will all be calculated with \code{na.rm = TRUE} and shown into the header_txt: \itemize{ \item{Mean, using \code{\link[base]{mean}}} \item{Standard Deviation, using \code{\link[stats]{sd}}} @@ -66,7 +69,7 @@ For numeric values of any class, these additional values will all be calculated \item{Outliers (total count and unique count), using \code{\link[grDevices]{boxplot.stats}}} } -For dates and times of any class, these additional values will be calculated with \code{na.rm = TRUE} and shown into the header: +For dates and times of any class, these additional values will be calculated with \code{na.rm = TRUE} and shown into the header_txt: \itemize{ \item{Oldest, using \code{\link{min}}} \item{Newest, using \code{\link{max}}, with difference between newest and oldest}