Convert any form (case or table form) into frequency form.

A wrapper for as.data.frame that is able to properly handle arrays. Converts object (obj) in case or table form into frequency form. The column containing the frequencies (freq) must be supplied if obj is already in frequency form (and you are using this function to select dimensions). Returns a tibble if tidy is set to TRUE.

Usage

as_freqform(obj, freq = NULL, dims = NULL, prop = NULL, tidy = TRUE)

Arguments

obj: Object to be converted to frequency form.
freq: If obj is already in frequency form, this is the name of the frequency column. If obj is in any other form, do not supply an argument (see "Details").
dims: A character vector of dimensions. If not specified, all variables apart from freq will be used as dimensions.
prop: If set to TRUE, the resulting "frequency" column will contain proportions (that sum to 1). May also be set to a character or numeric vector of dimensions to be used as margins from which proportions will be computed. The resulting "frequency" column is renamed to "Prop."
tidy: Returns a tibble if set to TRUE.

Value

Object in frequency form.

Details

Converts obj to a table using as_table before converting to frequency form

Author

Gavin M. Klorfine

Examples

library(vcdExtra)

data("HairEyeColor")

freqForm <- as.data.frame(HairEyeColor) # Generate frequency form data
tableForm <- as_table(HairEyeColor) # Generate table form data
arrayDat <- as_array(HairEyeColor) # Generate an array
caseForm <- as_caseform(HairEyeColor) # Generate case form data

# array -> frequency form
as_freqform(arrayDat) |> str()
#> tibble [32 × 4] (S3: tbl_df/tbl/data.frame)
#>  $ Hair: Factor w/ 4 levels "Black","Brown",..: 1 2 3 4 1 2 3 4 1 2 ...
#>  $ Eye : Factor w/ 4 levels "Brown","Blue",..: 1 1 1 1 2 2 2 2 3 3 ...
#>  $ Sex : Factor w/ 2 levels "Male","Female": 1 1 1 1 1 1 1 1 1 1 ...
#>  $ Freq: num [1:32] 32 53 10 3 11 50 10 30 10 25 ...

# table -> frequency form
as_freqform(tableForm) |> str()
#> tibble [32 × 4] (S3: tbl_df/tbl/data.frame)
#>  $ Hair: Factor w/ 4 levels "Black","Brown",..: 1 2 3 4 1 2 3 4 1 2 ...
#>  $ Eye : Factor w/ 4 levels "Brown","Blue",..: 1 1 1 1 2 2 2 2 3 3 ...
#>  $ Sex : Factor w/ 2 levels "Male","Female": 1 1 1 1 1 1 1 1 1 1 ...
#>  $ Freq: num [1:32] 32 53 10 3 11 50 10 30 10 25 ...

# case -> frequency form
as_freqform(caseForm) |> str()
#> tibble [32 × 4] (S3: tbl_df/tbl/data.frame)
#>  $ Hair: Factor w/ 4 levels "Black","Blond",..: 1 2 3 4 1 2 3 4 1 2 ...
#>  $ Eye : Factor w/ 4 levels "Blue","Brown",..: 1 1 1 1 2 2 2 2 3 3 ...
#>  $ Sex : Factor w/ 2 levels "Female","Male": 1 1 1 1 1 1 1 1 1 1 ...
#>  $ Freq: int [1:32] 9 64 34 7 36 4 66 16 2 8 ...

# Selecting dimensions (optional)
as_freqform(freqForm, freq = "Freq", dims = c("Hair", "Eye")) |> str()
#> tibble [16 × 3] (S3: tbl_df/tbl/data.frame)
#>  $ Hair: Factor w/ 4 levels "Black","Brown",..: 1 2 3 4 1 2 3 4 1 2 ...
#>  $ Eye : Factor w/ 4 levels "Brown","Blue",..: 1 1 1 1 2 2 2 2 3 3 ...
#>  $ Freq: num [1:16] 68 119 26 7 20 84 17 94 15 54 ...

as_freqform(tableForm, dims = c("Hair", "Eye")) |> str()
#> tibble [16 × 3] (S3: tbl_df/tbl/data.frame)
#>  $ Hair: Factor w/ 4 levels "Black","Brown",..: 1 2 3 4 1 2 3 4 1 2 ...
#>  $ Eye : Factor w/ 4 levels "Brown","Blue",..: 1 1 1 1 2 2 2 2 3 3 ...
#>  $ Freq: num [1:16] 68 119 26 7 20 84 17 94 15 54 ...

#-----For proportions-----#

as_freqform(tableForm, prop = TRUE) |> head() # print only Sex == Male rows
#> # A tibble: 6 × 4
#>   Hair  Eye   Sex      Prop
#>   <fct> <fct> <fct>   <dbl>
#> 1 Black Brown Male  0.0541 
#> 2 Brown Brown Male  0.0895 
#> 3 Red   Brown Male  0.0169 
#> 4 Blond Brown Male  0.00507
#> 5 Black Blue  Male  0.0186 
#> 6 Brown Blue  Male  0.0845 

# Marginalize proportions along "Sex" (i.e., male proportions sum to 1, female proportions sum to 1)
as_freqform(tableForm, prop = "Sex") |> head()
#> # A tibble: 6 × 4
#>   Hair  Eye   Sex     Prop
#>   <fct> <fct> <fct>  <dbl>
#> 1 Black Brown Male  0.115 
#> 2 Brown Brown Male  0.190 
#> 3 Red   Brown Male  0.0358
#> 4 Blond Brown Male  0.0108
#> 5 Black Blue  Male  0.0394
#> 6 Brown Blue  Male  0.179 

as_freqform(tableForm, prop = 3) |> head() # Same as above
#> # A tibble: 6 × 4
#>   Hair  Eye   Sex     Prop
#>   <fct> <fct> <fct>  <dbl>
#> 1 Black Brown Male  0.115 
#> 2 Brown Brown Male  0.190 
#> 3 Red   Brown Male  0.0358
#> 4 Blond Brown Male  0.0108
#> 5 Black Blue  Male  0.0394
#> 6 Brown Blue  Male  0.179 

# Marginalize proportions along multiple variables
as_freqform(tableForm, prop = c("Hair", "Sex")) |> head()
#> # A tibble: 6 × 4
#>   Hair  Eye   Sex     Prop
#>   <fct> <fct> <fct>  <dbl>
#> 1 Black Brown Male  0.571 
#> 2 Brown Brown Male  0.371 
#> 3 Red   Brown Male  0.294 
#> 4 Blond Brown Male  0.0652
#> 5 Black Blue  Male  0.196 
#> 6 Brown Blue  Male  0.350 

as_freqform(tableForm, prop = c(1, 3)) |> head() # Same as above
#> # A tibble: 6 × 4
#>   Hair  Eye   Sex     Prop
#>   <fct> <fct> <fct>  <dbl>
#> 1 Black Brown Male  0.571 
#> 2 Brown Brown Male  0.371 
#> 3 Red   Brown Male  0.294 
#> 4 Blond Brown Male  0.0652
#> 5 Black Blue  Male  0.196 
#> 6 Brown Blue  Male  0.350 

# Using dims and prop arguments in tandem
as_freqform(tableForm, dims = c("Hair", "Eye"), prop = TRUE)
#> # A tibble: 16 × 3
#>    Hair  Eye      Prop
#>    <fct> <fct>   <dbl>
#>  1 Black Brown 0.115  
#>  2 Brown Brown 0.201  
#>  3 Red   Brown 0.0439 
#>  4 Blond Brown 0.0118 
#>  5 Black Blue  0.0338 
#>  6 Brown Blue  0.142  
#>  7 Red   Blue  0.0287 
#>  8 Blond Blue  0.159  
#>  9 Black Hazel 0.0253 
#> 10 Brown Hazel 0.0912 
#> 11 Red   Hazel 0.0236 
#> 12 Blond Hazel 0.0169 
#> 13 Black Green 0.00845
#> 14 Brown Green 0.0490 
#> 15 Red   Green 0.0236 
#> 16 Blond Green 0.0270