crosstabs: Display Cross Table of Two Variables
In qol: Powerful 'SAS' Inspired Concepts for more Efficient Bigger Outputs

crosstabs

R Documentation

Display Cross Table of Two Variables

Description

crosstabs() produces a cross table of two variables. Statistics can be weighted sums, unweighted frequencies or different percentages.

Usage

crosstabs(
  data_frame,
  rows,
  columns,
  show_total = TRUE,
  statistics = "sum",
  formats = c(),
  by = c(),
  weight = NULL,
  titles = .qol_options[["titles"]],
  footnotes = .qol_options[["footnotes"]],
  style = .qol_options[["excel_style"]],
  output = .qol_options[["output"]],
  na.rm = .qol_options[["na.rm"]],
  print_miss = .qol_options[["print_miss"]],
  print = .qol_options[["print"]],
  monitor = .qol_options[["monitor"]]
)

Arguments

`data_frame`	A data frame in which are the variables to tabulate.
`rows`	The variable that appears in the table rows.
`columns`	The variable that appears in the table columns.
`show_total`	TRUE by default. Whether to print row and column totals or not.
`statistics`	The user requested statistics.Available functions: "sum" -> Weighted and unweighted sum "freq" -> Unweighted frequency "pct_row" -> Weighted and unweighted row percentages "pct_column" -> Weighted and unweighted column percentages "pct_total" -> Weighted and unweighted percentages compared to the grand total
`formats`	A list in which is specified which formats should be applied to which variables.
`by`	Compute tables stratified by the expressions of the provided variables.
`weight`	Put in a weight variable to compute weighted results.
`titles`	Specify one or more table titles.
`footnotes`	Specify one or more table footnotes.
`style`	A list of options can be passed to control the appearance of 'Excel' outputs. Styles can be created with `excel_output_style()`.
`output`	The following output formats are available: console (default), text, excel and excel_nostyle.
`na.rm`	FALSE by default. If TRUE removes all NA values from the variables.
`print_miss`	FALSE by default. If TRUE outputs all possible categories of the grouping variables based on the provided formats, even if there are no observations for a combination.
`print`	TRUE by default. If TRUE prints the output, if FALSE doesn't print anything. Can be used if one only wants to catch the output data frame.
`monitor`	FALSE by default. If TRUE, outputs two charts to visualize the functions time consumption.

Details

crosstabs() is based on the 'SAS' procedure Proc Freq, which provides efficient and readable ways to perform cross tabulations.

To create a cross table you only need to provide a variable for the rows and columns. Nothing special about this. The real power comes into play, when you output your tables as a fully styled 'Excel' workbook. Setting up a custom, reusable style is as easy as setting up options like: provide a color for the table header, set the font size for the row header, should borders be drawn for the table cells yes/no, and so on.

You can not only output sums and frequencies, but also different percentages, all set up in separate, evenly designed tables. For just a quick overview, rather than fully designed tables, you can also just output the tables in ASCII style format.

Value

Returns a data tables containing the results for the cross table.

Examples

# Example data frame
my_data <- dummy_data(1000)

# Define titles and footnotes. If you want to add hyperlinks you can do so by
# adding "link:" followed by the hyperlink to the main text.
set_titles("This is title number 1 link: https://cran.r-project.org/",
           "This is title number 2",
           "This is title number 3")

set_footnotes("This is footnote number 1",
              "This is footnote number 2",
              "This is footnote number 3 link: https://cran.r-project.org/")

# Output cross tables
my_data |> crosstabs(age, sex)
my_data |> crosstabs(age, sex,
                     weight = "weight")

# Also works with characters
my_data |> crosstabs("age", "sex")
my_data |> crosstabs("age", "sex",
                     weight = "weight")

# Applying formats
age. <- discrete_format(
    "Total"          = 0:100,
    "under 18"       = 0:17,
    "18 to under 25" = 18:24,
    "25 to under 55" = 25:54,
    "55 to under 65" = 55:64,
    "65 and older"   = 65:100)

sex. <- discrete_format(
    "Total"  = 1:2,
    "Male"   = 1,
    "Female" = 2)

my_data |> crosstabs(age, sex,
                     formats   = list(age = age., sex = sex.))

# Split cross table by expressions of another variable
my_data |> crosstabs(age, sex, by = education)

# Compute different stats
my_data |> crosstabs(age, sex,
                     statistics = c("sum", "freq", "pct_row", "pct_column", "pct_total"))

# Get a list with two data tables for further usage
result_list <- my_data |> crosstabs(age, sex,
                                    formats = list(age = age., sex = sex.))

# Output in text file
my_data |> crosstabs(age, sex, output = "text")

# Output to Excel
my_data |> crosstabs(age, sex, output = "excel")

# Individual styling can also be passed directly
my_style <- excel_output_style(header_back_color = "0077B6",
                               font              = "Times New Roman")

my_data |> crosstabs(age, sex, output = "excel", style = my_style)

# To save a table as xlsx file you have to set the path and filename in the
# style element
# Example files paths
table_file <- tempfile(fileext = ".xlsx")

# Note: Normally you would directly input the path ("C:/MyPath/") and name ("MyFile.xlsx").
set_style_options(save_path  = dirname(table_file),
                  file       = basename(table_file),
                  sheet_name = "MyTable")

my_data |> crosstabs(age, sex, output = "excel")

# Manual cleanup for example
unlink(table_file)

# Global options are permanently active until the current R session is closed.
# There are also functions to reset the values manually.
reset_style_options()
reset_qol_options()
close_file()

qol documentation built on March 11, 2026, 1:06 a.m.