| freq | R Documentation |
Create a frequency table of a vector or a data.frame. It supports tidyverse's quasiquotation and RMarkdown for reports. Easiest practice is: data %>% freq(var) using the tidyverse.
top_freq can be used to get the top/bottom n items of a frequency table, with counts as names. It respects ties.
freq(x, ...)
## Default S3 method:
freq(
x,
sort.count = TRUE,
nmax = getOption("max.print.freq"),
na.rm = TRUE,
row.names = TRUE,
markdown = !interactive(),
digits = 2,
quote = NULL,
header = TRUE,
title = NULL,
na = "<NA>",
sep = " ",
decimal.mark = getOption("OutDec"),
big.mark = "",
wt = NULL,
...
)
## S3 method for class 'factor'
freq(x, ..., droplevels = FALSE)
## S3 method for class 'matrix'
freq(x, ..., quote = FALSE)
## S3 method for class 'table'
freq(x, ..., sep = " ")
## S3 method for class 'numeric'
freq(x, ..., digits = 2)
## S3 method for class 'Date'
freq(x, ..., format = "yyyy-mm-dd")
## S3 method for class 'hms'
freq(x, ..., format = "HH:MM:SS")
is.freq(f)
top_freq(f, n)
header(f, property = NULL)
## S3 method for class 'freq'
print(
x,
nmax = getOption("max.print.freq", default = 10),
markdown = !interactive(),
header = TRUE,
decimal.mark = getOption("OutDec"),
big.mark = ifelse(decimal.mark != ",", ",", "."),
...
)
x |
vector of any class or a |
... |
up to nine different columns of |
sort.count |
sort on count, i.e. frequencies. This will be |
nmax |
number of row to print. The default, |
na.rm |
a logical value indicating whether |
row.names |
a logical value indicating whether row indices should be printed as |
markdown |
a logical value indicating whether the frequency table should be printed in markdown format. This will print all rows (except when |
digits |
how many significant digits are to be used for numeric values in the header (not for the items themselves, that depends on |
quote |
a logical value indicating whether or not strings should be printed with surrounding quotes. Default is to print them only around characters that are actually numeric values. |
header |
a logical value indicating whether an informative header should be printed |
title |
text to show above frequency table, at default to tries to coerce from the variables passed to |
na |
a character string that should be used to show empty ( |
sep |
a character string to separate the terms when selecting multiple columns |
decimal.mark |
the character to be used to indicate the numeric decimal point |
big.mark |
character; if not empty used as mark between every 'big.interval' decimals before (hence big) the decimal point |
wt |
frequency weights. If a variable, computes |
droplevels |
a logical value indicating whether in factors empty levels should be dropped |
format |
a character to define the printing format (it supports |
f |
a frequency table |
n |
number of top n items to return, use -n for the bottom n items. It will include more than |
property |
property in header to return this value directly |
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.
Input can be done in many different ways. Base R methods are:
freq(df$variable) freq(df[, "variable"])
Tidyverse methods are:
df$variable %>% freq()
df[, "variable"] %>% freq()
df %>% freq("variable")
df %>% freq(variable)
For numeric values of any class, these additional values will all be calculated with na.rm = TRUE and shown into the header:
Mean, using mean
Standard Deviation, using sd
Coefficient of Variation (CV), the standard deviation divided by the mean
Mean Absolute Deviation (MAD), using mad
Tukey Five-Number Summaries (minimum, Q1, median, Q3, maximum), see NOTE below
Interquartile Range (IQR) calculated as Q3 - Q1, see NOTE below
Coefficient of Quartile Variation (CQV, sometimes called coefficient of dispersion) calculated as (Q3 - Q1) / (Q3 + Q1), see NOTE below
Outliers (total count and percentage), using boxplot.stats
NOTE: These values are calculated using the same algorithm as used by Minitab and SPSS: p[k] = E[F(x[k])]. See Type 6 on the quantile page.
For dates and times of any class, these additional values will be calculated with na.rm = TRUE and shown into the header:
Oldest, using min
Newest, using max, with difference between newest and oldest
In factors, all factor levels that are not existing in the input data will be dropped at default.
The function top_freq will include more than n rows if there are ties. Use a negative number for n (like n = -3) to select the bottom n values.
A data.frame (with an additional class "freq") with five columns: item, count, percent, cum_count and cum_percent.
freq() functionInterested in extending the freq() function with your own class? Add a method like below to your package, and optionally define some header info by passing a list to the .add_header parameter, like below example for class difftime. This example assumes that you use the roxygen2 package for package development.
#' @method freq difftime
#' @importFrom cleaner freq.default
#' @export
#' @noRd
freq.difftime <- function(x, ...) {
freq.default(x = x, ...,
.add_header = list(units = attributes(x)$units))
}
Be sure to call freq.default in your function and not just freq. Also, add cleaner to the Imports: field of your DESCRIPTION file, to make sure that it will be installed with your package, e.g.:
Imports: cleaner
freq(unclean$gender, markdown = FALSE)
freq(x = clean_factor(unclean$gender,
levels = c("^m" = "Male",
"^f" = "Female")),
markdown = TRUE,
title = "Frequencies of a cleaned version for a markdown report!",
header = FALSE,
quote = TRUE)
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