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Display Cross Table of Two Variables

Source: R/crosstabs.R
crosstabs.Rd

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

Usage

crosstabs(
  data_frame,
  rows,
  columns,
  statistics = c("sum"),
  formats = c(),
  by = c(),
  weight = NULL,
  titles = c(),
  footnotes = c(),
  style = excel_output_style(),
  output = "console",
  na.rm = FALSE,
  print = TRUE,
  monitor = FALSE
)

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.

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

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.

Value

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

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.

See also

Creating a custom table style: excel_output_style(), modify_output_style(), number_format_style(), modify_number_formats().

Creating formats: discrete_format() and interval_format().

Functions that can handle formats and styles: frequencies(), any_table().

Additional functions that can handle styles: export_with_style()

Additional functions that can handle formats: summarise_plus(), recode(), recode_multi()

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.
titles <- c("This is title number 1 link: https://cran.r-project.org/",
            "This is title number 2",
            "This is title number 3")
footnotes <- c("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 and titles
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.),
                     titles    = titles,
                     footnotes = footnotes)

# 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")

# With individual styling
my_style <- excel_output_style(header_back_color = "0077B6",
                               font              = "Times New Roman")

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