freq: Frequency Table

Description

Creates a frequency table for a vector or variable from a data frame, with options for weighting, sorting, handling labelled data, defining custom missing values, and displaying cumulative percentages.

When styled = TRUE, the function prints a spicy-formatted ASCII table using print.spicy_freq_table() and spicy_print_table(); otherwise, it returns a data.frame containing frequencies and proportions.

Usage

freq(
  data,
  x = NULL,
  weights = NULL,
  digits = 1,
  valid = TRUE,
  cum = FALSE,
  sort = "",
  na_val = NULL,
  labelled_levels = c("prefixed", "labels", "values", "p", "l", "v"),
  rescale = TRUE,
  styled = TRUE,
  ...
)

Value

A data.frame with columns:

value - unique values or factor levels
n - frequency count (weighted if applicable)
prop - proportion of total
valid_prop - proportion of valid responses (if valid = TRUE)
cum_prop, cum_valid_prop - cumulative percentages (if cum = TRUE)

If styled = TRUE, prints the formatted table to the console and returns it invisibly.

Arguments

data

A data.frame, vector, or factor. If a data frame is provided, specify the target variable x.

x

A variable from data (unquoted).

weights

Optional numeric vector of weights (same length as x). The variable may be referenced as a bare name when it belongs to data.

digits

Number of decimal digits to display for percentages (default: 1).

valid

Logical. If TRUE (default), display valid percentages (excluding missing values).

cum

Logical. If FALSE (the default), cumulative percentages are omitted. If TRUE, adds cumulative percentages.

sort

Sorting method for values:

"" - no sorting (default)
"+" - increasing frequency
"-" - decreasing frequency
"name+" - alphabetical A-Z
"name-" - alphabetical Z-A

na_val

Vector of numeric or character values to be treated as missing (NA).

For labelled variables (from haven or labelled), this argument must refer to the underlying coded values, not the visible labels.

Example:

x <- labelled(c(1, 2, 3, 1, 2, 3), c("Low" = 1, "Medium" = 2, "High" = 3))
freq(x, na_val = 1) # Treat all "Low" as missing

labelled_levels

For labelled variables, defines how labels and values are displayed:

"prefixed" or "p" - show labels as [value] label (default)
"labels" or "l" - show only labels
"values" or "v" - show only numeric codes

rescale

Logical. If TRUE (default), rescale weights so that their total equals the unweighted sample size.

styled

Logical. If TRUE (default), print the formatted spicy table. If FALSE, return a plain data.frame with frequency values.

...

Additional arguments passed to print.spicy_freq_table().

Details

This function is designed to mimic common frequency procedures from statistical software such as SPSS or Stata, while integrating the flexibility of R's data structures.

It automatically detects the type of input (vector, factor, or labelled) and applies appropriate transformations, including:

Handling of labelled variables via labelled or haven
Optional recoding of specific values as missing (na_val)
Optional weighting with a rescaling mechanism
Support for cumulative percentages (cum = TRUE)
Multiple display modes for labels via labelled_levels

When weighting is applied (weights), the frequencies and percentages are computed proportionally to the weights. The argument rescale = TRUE normalizes weights so their sum equals the unweighted sample size.

Examples

Run this code

# Frequency table with labelled ordered factor
freq(sochealth, education)
freq(sochealth, self_rated_health, sort = "-")

library(labelled)

# Simple numeric vector
x <- c(1, 2, 2, 3, 3, 3, NA)
freq(x)

# Labelled variable (haven-style)
x_lbl <- labelled(
  c(1, 2, 3, 1, 2, 3, 1, 2, NA),
  labels = c("Low" = 1, "Medium" = 2, "High" = 3)
)
var_label(x_lbl) <- "Satisfaction level"

# Treat value 1 ("Low") as missing
freq(x_lbl, na_val = 1)

# Display only labels, add cumulative %
freq(x_lbl, labelled_levels = "labels", cum = TRUE)

# Display values only, sorted descending
freq(x_lbl, labelled_levels = "values", sort = "-")

# With weighting
df <- data.frame(
  sexe = factor(c("Male", "Female", "Female", "Male", NA, "Female")),
  poids = c(12, 8, 10, 15, 7, 9)
)

# Weighted frequencies (normalized)
freq(df, sexe, weights = poids, rescale = TRUE)

# Weighted frequencies (without rescaling)
freq(df, sexe, weights = poids, rescale = FALSE)

# Base R style, with weights and cumulative percentages
freq(df$sexe, weights = df$poids, cum = TRUE)

# Piped version (tidy syntax) and sort alphabetically descending ("name-")
df |> freq(sexe, sort = "name-")

# Non-styled return (for programmatic use)
f <- freq(df, sexe, styled = FALSE)
head(f)