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na freq, removed factors

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dr. M.S. (Matthijs) Berends 2018-10-23 09:42:26 +02:00
parent 9c56257da1
commit 299c5bea43
4 changed files with 76 additions and 115 deletions
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2
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR
Version: 0.4.0.9006
Date: 2018-10-22
Date: 2018-10-23
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(

2
NEWS.md
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@ -22,7 +22,9 @@
* Check for `hms::is.hms` in frequency tables (`freq()`)
* New parameter `header` for frequency tables to turn them off (default when `markdown = TRUE`)
* Freq now prints in markdown at default in non-interactive sessions
* Freq no longer add the factor level column and sorts factors on count again
* Removed diacritics from all authors (columns `microorganisms$ref` and `microorganisms.old$ref`) to comply with CRAN policy to only allow ASCII characters
* Freq gained `na` parameter, to choose with character to print for empty values
* Fix for `mo_property` not working properly
* Fix for `EUCAST_rules` where some Streptococci would become ceftazidime R in EUCAST rule 4.5
* Support for class `difftime` in frequency tables

126
R/freq.R
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@ -23,12 +23,13 @@
#' @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 (if set) 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 a logical value indicating whether the frequency table should be printed in markdown format. This will print all rows and is default behaviour in non-interactive R sessions (like when knitting RMarkdown files).
#' @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 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 na a character string to should be used to show empty (\code{NA}) values (only useful when \code{na.rm = FALSE})
#' @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.
@ -150,6 +151,7 @@ frequency_tbl <- function(x,
digits = 2,
quote = FALSE,
header = !markdown,
na = "<NA>",
sep = " ") {
mult.columns <- 0
@ -197,7 +199,7 @@ frequency_tbl <- function(x,
# now this DF contains 3 columns: the 2 vars and a Freq column
# paste the first 2 cols and repeat them Freq times:
x <- rep(x = do.call(paste, c(x[colnames(x)[1:2]], sep = sep)),
times = x$Freq)
times = x$Freq)
x.name <- "a `table` object"
cols <- NULL
#mult.columns <- 2
@ -229,9 +231,8 @@ frequency_tbl <- function(x,
class(x) <- x_class
}
if (missing(sort.count) & 'factor' %in% class(x)) {
# sort on factor level at default when x is a factor and sort.count is not set
sort.count <- FALSE
if (sort.count == FALSE & 'factor' %in% class(x)) {
# warning("Sorting a factor sorts on factor level, not necessarily alphabetically.", call. = FALSE)
}
header_txt <- character(0)
@ -260,11 +261,11 @@ frequency_tbl <- function(x,
}
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(), ')')
' (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_txt <- header_txt %>% paste0(markdown_line, '\nUnique: ', x %>% n_distinct() %>% format())
if (NROW(x) > 0 & any(class(x) == "character")) {
@ -287,11 +288,11 @@ frequency_tbl <- function(x,
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), ')')
' (CV: ', x %>% cv(na.rm = TRUE) %>% format(digits = digits),
', MAD: ', x %>% stats::mad(na.rm = TRUE) %>% format(digits = digits), ')')
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), ')')
' (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_txt <- header_txt %>% paste0(markdown_line, '\nOutliers: ', outlier_length)
if (outlier_length > 0) {
@ -300,14 +301,14 @@ frequency_tbl <- function(x,
}
if (NROW(x) > 0 & any(class(x) == "rsi")) {
header_txt <- header_txt %>% paste0('\n')
cnt_S <- sum(x == "S")
cnt_I <- sum(x == "I")
cnt_R <- sum(x == "R")
cnt_S <- sum(x == "S", na.rm = TRUE)
cnt_I <- sum(x == "I", na.rm = TRUE)
cnt_R <- sum(x == "R", na.rm = TRUE)
header_txt <- header_txt %>% paste(markdown_line, '\n%IR: ',
((cnt_I + cnt_R) / sum(!is.na(x))) %>% percent(force_zero = TRUE, round = digits))
((cnt_I + cnt_R) / sum(!is.na(x), na.rm = TRUE)) %>% percent(force_zero = TRUE, round = digits))
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))
(cnt_I / cnt_S) %>% format(digits = 1, nsmall = 1), " : ",
(cnt_R / cnt_S) %>% format(digits = 1, nsmall = 1))
}
formatdates <- "%e %B %Y" # = d mmmm yyyy
@ -327,15 +328,15 @@ frequency_tbl <- function(x,
# hms
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.)')
' (+', difftime(maxdate, mindate, units = 'mins') %>% as.double() %>% format(digits = digits), ' min.)')
} else {
# other date formats
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), ')')
' (+', difftime(maxdate, mindate, units = 'auto') %>% as.double() %>% format(digits = digits), ')')
}
header_txt <- header_txt %>% paste0(markdown_line, '\nMedian: ', mediandate %>% format(formatdates) %>% trimws(),
' (~', percent(median_days / maxdate_days, round = 0), ')')
' (~', percent(median_days / maxdate_days, round = 0), ')')
}
if (any(class(x) == 'POSIXlt')) {
x <- x %>% format(formatdates)
@ -354,23 +355,14 @@ frequency_tbl <- function(x,
}
# create table with counts and percentages
column_names <- c('Item', 'Count', 'Percent', 'Cum. Count', 'Cum. Percent', '(Factor Level)')
column_names_df <- c('item', 'count', 'percent', 'cum_count', 'cum_percent', 'factor_level')
column_names <- c('Item', 'Count', 'Percent', 'Cum. Count', 'Cum. Percent')
column_names_df <- c('item', 'count', 'percent', 'cum_count', 'cum_percent')
if (any(class(x) == 'factor')) {
df <- tibble(item = x,
fctlvl = x %>% as.integer()) %>%
group_by(item, fctlvl)
column_align <- c('l', 'r', 'r', 'r', 'r', 'r')
} else {
df <- tibble(item = x) %>%
group_by(item)
# strip factor lvl from col names
column_names <- column_names[1:length(column_names) - 1]
column_names_df <- column_names_df[1:length(column_names_df) - 1]
column_align <- c(x_align, 'r', 'r', 'r', 'r')
}
df <- df %>% summarise(count = n())
df <- tibble(item = x) %>%
group_by(item) %>%
summarise(count = n())
column_align <- c(x_align, 'r', 'r', 'r', 'r')
if (df$item %>% paste(collapse = ',') %like% '\033') {
# remove escape char
@ -382,11 +374,7 @@ frequency_tbl <- function(x,
if (sort.count == TRUE) {
df <- df %>% arrange(desc(count), item)
} else {
if (any(class(x) == 'factor')) {
df <- df %>% arrange(fctlvl, item)
} else {
df <- df %>% arrange(item)
}
df <- df %>% arrange(item)
}
if (quote == TRUE) {
@ -399,34 +387,27 @@ frequency_tbl <- function(x,
df$cum_count <- base::cumsum(df$count)
df$cum_percent <- df$cum_count / base::sum(df$count, na.rm = TRUE)
if (any(class(x) == 'factor')) {
# put factor last
df <- df %>% select(item, count, percent, cum_count, cum_percent, fctlvl)
}
colnames(df) <- column_names_df
class(df) <- c('frequency_tbl', class(df))
attr(df, 'package') <- 'AMR'
if (markdown == TRUE) {
tbl_format <- 'markdown'
} else {
tbl_format <- 'pandoc'
}
attr(df, 'opt') <- list(data = x.name,
vars = cols,
header = header,
header_txt = header_txt,
row_names = row.names,
column_names = column_names,
column_align = column_align,
tbl_format = tbl_format,
nmax = nmax,
nmax.set = nmax.set)
df
structure(.Data = df,
class = c('frequency_tbl', class(df)),
opt = list(data = x.name,
vars = cols,
header = header,
header_txt = header_txt,
row_names = row.names,
column_names = column_names,
column_align = column_align,
tbl_format = tbl_format,
na = na,
nmax = nmax,
nmax.set = nmax.set))
}
#' @rdname freq
@ -547,7 +528,7 @@ print.frequency_tbl <- function(x, nmax = getOption("max.print.freq", default =
if (opt$tbl_format == "pandoc") {
title <- bold(title)
} else if (opt$tbl_format == "markdown") {
title <- paste0("**", title, "**")
title <- paste0("**", title, "**")
}
if (opt$header == TRUE) {
@ -571,7 +552,10 @@ print.frequency_tbl <- function(x, nmax = getOption("max.print.freq", default =
# save old NA setting for kable
opt.old <- options()$knitr.kable.NA
options(knitr.kable.NA = "<NA>")
if (is.null(opt$na)) {
opt$na <- "<NA>"
}
options(knitr.kable.NA = opt$na)
if (nrow(x) > opt$nmax & opt$tbl_format != "markdown") {
@ -615,6 +599,10 @@ print.frequency_tbl <- function(x, nmax = getOption("max.print.freq", default =
x$cum_count <- format(x$cum_count)
x$cum_percent <- percent(x$cum_percent, force_zero = TRUE)
if (opt$tbl_format == "markdown") {
cat("\n\n")
}
print(
knitr::kable(x,
format = opt$tbl_format,
@ -628,7 +616,11 @@ print.frequency_tbl <- function(x, nmax = getOption("max.print.freq", default =
cat(footer)
}
cat('\n')
if (opt$tbl_format == "markdown") {
cat("\n\n")
} else {
cat('\n')
}
# reset old kable setting
options(knitr.kable.NA = opt.old)

61
README.md
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@ -361,69 +361,36 @@ freq(mydata$myvariable)
mydata %>% freq(myvariable)
```
Factors sort on item by default:
Frequency are of course sorted by count at default:
```r
septic_patients %>% freq(hospital_id)
# Frequency table of `hospital_id`
# Class: factor (numeric)
# Length: 2000 (of which NA: 0 = 0.00%)
# Unique: 4
#
# Item Count Percent Cum. Count Cum. Percent (Factor Level)
# --- ----- ------ -------- ----------- ------------- ---------------
# 1 A 321 16.1% 321 16.1% 1
# 2 B 663 33.1% 984 49.2% 2
# 3 C 254 12.7% 1238 61.9% 3
# 4 D 762 38.1% 2000 100.0% 4
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------ -------- ----------- -------------
# 1 D 762 38.1% 762 38.1%
# 2 B 663 33.1% 1425 71.2%
# 3 A 321 16.1% 1746 87.3%
# 4 C 254 12.7% 2000 100.0%
```
This can be changed with the `sort.count` parameter:
```r
septic_patients %>% freq(hospital_id, sort.count = TRUE)
# Frequency table of `hospital_id`
septic_patients %>% freq(hospital_id, sort.count = FALSE)
# Class: factor (numeric)
# Length: 2000 (of which NA: 0 = 0.00%)
# Unique: 4
#
# Item Count Percent Cum. Count Cum. Percent (Factor Level)
# --- ----- ------ -------- ----------- ------------- ---------------
# 1 D 762 38.1% 762 38.1% 4
# 2 B 663 33.1% 1425 71.2% 2
# 3 A 321 16.1% 1746 87.3% 1
# 4 C 254 12.7% 2000 100.0% 3
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------ -------- ----------- -------------
# 1 A 321 16.1% 321 16.1%
# 2 B 663 33.1% 984 49.2%
# 3 C 254 12.7% 1238 61.9%
# 4 D 762 38.1% 2000 100.0%
```
All other types, like numbers, characters and dates, sort on count by default:
```r
septic_patients %>% freq(date)
# Frequency table of `date`
# Class: Date
# Length: 2000 (of which NA: 0 = 0.0%)
# Unique: 1151
#
# Oldest: 2 January 2002
# Newest: 28 December 2017 (+5839)
# Median: 31 July 2009 (~47%)
#
# Item Count Percent Cum. Count Cum. Percent
# --- ----------- ------ -------- ----------- -------------
# 1 2016-05-21 10 0.5% 10 0.5%
# 2 2004-11-15 8 0.4% 18 0.9%
# 3 2013-07-29 8 0.4% 26 1.3%
# 4 2017-06-12 8 0.4% 34 1.7%
# 5 2015-11-19 7 0.4% 41 2.1%
# 6 2005-12-22 6 0.3% 47 2.4%
# 7 2015-10-12 6 0.3% 53 2.6%
# 8 2002-02-27 5 0.2% 58 2.9%
# 9 2003-10-20 5 0.2% 63 3.1%
# 10 2004-02-02 5 0.2% 68 3.4%
# 11 2004-02-18 5 0.2% 73 3.6%
# 12 2004-06-22 5 0.2% 78 3.9%
# 13 2004-12-01 5 0.2% 83 4.2%
# 14 2005-08-16 5 0.2% 88 4.4%
# 15 2005-09-01 5 0.2% 93 4.7%
# [ reached getOption("max.print.freq") -- omitted 1136 entries, n = 1907 (95.3%) ]
```
For numeric values, some extra descriptive statistics will be calculated:
```r
freq(runif(n = 10, min = 1, max = 5))