HTML summary table

Renders a HTML table ready for plonking into a HTML or word document.

Usage

proc_freq(var1, data = NULL, sort = NULL, min.frq = 0)

Arguments

var1

Name of the variable

data

Dataset that contains var1

sort

Optional argument which can take on "asc" or "desc" to indicate the type of sort required.

min.frq

Minimum frequency

Value

Dataframe

Details

Renders output similar to the "proc freq" function of SAS.

Created by PV (2023).

Examples

test = iris
proc_freq(Species, test)
 
Species
Species
Frequency
Percent
Cumulative Frequency
Cumulative Percent
setosa
50
33.3
50
33.3
versicolor
50
33.3
100
66.7
virginica
50
33.3
150
100.0
Frequency Missing = 0
 
 
Species
Species
Frequency
Percent
Cumulative Frequency
Cumulative Percent
setosa
50
33.3
50
33.3
versicolor
50
33.3
100
66.7
virginica
50
33.3
150
100.0
Frequency Missing = 0
 
 
Species
Species
Frequency
Percent
Cumulative Frequency
Cumulative Percent
setosa
50
33.3
50
33.3
versicolor
50
33.3
100
66.7
virginica
50
33.3
150
100.0
Frequency Missing = 0
test[1:4, "Species"] <- NA
proc_freq(Species, test)
 
Species
Species
Frequency
Percent
Cumulative Frequency
Cumulative Percent
setosa
46
31.5
46
31.5
versicolor
50
34.2
96
65.8
virginica
50
34.2
146
100.0
Frequency Missing = 4
 
 
Species
Species
Frequency
Percent
Cumulative Frequency
Cumulative Percent
setosa
46
31.5
46
31.5
versicolor
50
34.2
96
65.8
virginica
50
34.2
146
100.0
Frequency Missing = 4
 
 
Species
Species
Frequency
Percent
Cumulative Frequency
Cumulative Percent
setosa
46
31.5
46
31.5
versicolor
50
34.2
96
65.8
virginica
50
34.2
146
100.0
Frequency Missing = 4