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Converts a frequency table, given either as a table object or a data frame in frequency form to a data frame representing individual observations in the table.

Usage

expand.dft(x, var.names = NULL, freq = "Freq", ...)

expand.table(x, var.names = NULL, freq = "Freq", ...)

Arguments

x

A table object, or a data frame in frequency form containing factors and one numeric variable representing the cell frequency for that combination of factors.

var.names

A list of variable names for the factors, if you wish to override those already in the table

freq

The name of the frequency variable in the table

...

Other arguments passed down to type.convert. In particular, pay attention to na.strings (default: na.strings=NA if there are missing cells) and as.is (default: as.is=FALSE, converting character vectors to factors).

Details

expand.table is a synonym for expand.dft.

Value

A data frame containing the factors in the table and as many observations as are represented by the total of the freq variable.

References

Originally posted on R-Help, Jan 20, 2009, http://tolstoy.newcastle.edu.au/R/e6/help/09/01/1873.html

Friendly, M. and Meyer, D. (2016). Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data. Boca Raton, FL: Chapman & Hall/CRC. http://ddar.datavis.ca.

Author

Mark Schwarz

Examples

library(vcd)
art <- xtabs(~Treatment + Improved, data = Arthritis)
art
#>          Improved
#> Treatment None Some Marked
#>   Placebo   29    7      7
#>   Treated   13    7     21
artdf <- expand.dft(art)
str(artdf)
#> 'data.frame':	84 obs. of  2 variables:
#>  $ Treatment: chr  "Placebo" "Placebo" "Placebo" "Placebo" ...
#>  $ Improved : chr  "None" "None" "None" "None" ...

# 1D case
(tab <- table(sample(head(letters), 20, replace=TRUE)))
#> 
#> a b c d e f 
#> 4 4 3 3 3 3 
expand.table(tab, var.names="letter")
#>    letter
#> 1       a
#> 2       a
#> 3       a
#> 4       a
#> 5       b
#> 6       b
#> 7       b
#> 8       b
#> 9       c
#> 10      c
#> 11      c
#> 12      d
#> 13      d
#> 14      d
#> 15      e
#> 16      e
#> 17      e
#> 18      f
#> 19      f
#> 20      f