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114 lines
4.4 KiB
R
Executable File
114 lines
4.4 KiB
R
Executable File
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/freq.R
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\name{freq}
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\alias{freq}
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\alias{frequency_tbl}
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\alias{top_freq}
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\title{Frequency table}
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\usage{
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frequency_tbl(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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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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sep = " ")
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top_freq(f, n)
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}
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\arguments{
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\item{x}{vector with items, or \code{data.frame}}
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\item{...}{up to nine different columns of \code{x} to calculate frequencies from, see Examples}
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\item{sort.count}{sort on count, i.e. frequencies. Use \code{FALSE} to sort alphabetically on item.}
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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 = NULL} or \code{nmax = NA} to print all rows.}
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\item{na.rm}{a logical value indicating whether 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{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{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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\item{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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}
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\value{
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A \code{data.frame} with an additional class \code{"frequency_tbl"}
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}
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\description{
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Create a frequency table of a vector with items or a data frame. Supports quasiquotation and markdown for reports. \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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}
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\details{
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This package also has a vignette available about this function, run: \code{browseVignettes("AMR")} to read it.
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For numeric values of any class, these additional values will be calculated 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{Five numbers of Tukey (min, Q1, median, Q3, max), using \code{\link[stats]{fivenum}}}
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\item{Outliers (total count and unique count), using \code{\link{boxplot.stats}}}
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\item{Coefficient of variation (CV), the standard deviation divided by the mean}
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\item{Coefficient of quartile variation (CQV, sometimes called coefficient of dispersion), calculated as \code{(Q3 - Q1) / (Q3 + Q1)} using \code{\link{quantile}} with \code{type = 6} as quantile algorithm to comply with SPSS standards}
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}
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For dates and times of any class, these additional values will be calculated and shown into the header:
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\itemize{
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\item{Oldest, using \code{\link[base]{min}}}
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\item{Newest, using \code{\link[base]{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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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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}
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\examples{
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library(dplyr)
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# this all gives the same result:
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freq(septic_patients$hospital_id)
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freq(septic_patients[, "hospital_id"])
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septic_patients$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 when used to tidyverse
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# you could use `select`...
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septic_patients \%>\%
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filter(hospital_id == "A") \%>\%
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select(bactid) \%>\%
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freq()
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# ... or you use `freq` to select it immediately
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septic_patients \%>\%
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filter(hospital_id == "A") \%>\%
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freq(bactid)
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# select multiple columns; they will be pasted together
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septic_patients \%>\%
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left_join_microorganisms \%>\%
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filter(hospital_id == "A") \%>\%
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freq(genus, species)
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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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years \%>\% pull(item)
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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(bactid) \%>\%
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top_freq(10)
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}
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\keyword{freq}
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\keyword{frequency}
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\keyword{summarise}
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\keyword{summary}
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