Coerce to a Data Frame

Coerce to a Data Frame

Usage

# S4 method for class 'CompositionMatrix'
as.data.frame(x, ..., group_var = ".group", group_after = 0)

# S4 method for class 'LogRatio'
as.data.frame(x, ..., group_var = ".group", group_after = 0)

# S4 method for class 'OutlierIndex'
as.data.frame(x, row.names = rownames(x), optional = FALSE, ...)

Arguments

x

An R object (typically, a CompositionMatrix object).

...

Further parameters to be passed to as.data.frame().

group_var

A character string specifying the name of the column to create for group attribution (only used if x is grouped).

group_after

An integer specifying a subscript, after which the new group_var column is to be appended (only used if x is grouped).

row.names

A character vector giving the row names for the data frame, or NULL.

optional

A logical scalar: should the names of the variables in the data frame be checked? If FALSE then the names of the variables in the data frame are checked to ensure that they are syntactically valid variable names and are not duplicated.

Value

A data.frame.

See also

Other mutators: labels(), totals(), weights()

Author

N. Frerebeau

Examples

## Create a count matrix
A1 <- matrix(data = sample(1:100, 100, TRUE), nrow = 20)

## Coerce to compositions
B <- as_composition(A1)

## Row sums are internally stored before coercing to relative frequencies
totals(B)
#>  [1] 179 222 225 106 264 280 245 264 297 147 212 226 251 190 248 305 140 229 193
#> [20] 340

## This allows to restore the source data
A2 <- as_amounts(B)

## Coerce to a data.frame
X <- as.data.frame(B)
head(X)
#>            V1         V2         V3         V4         V5
#> S1 0.13407821 0.48044693 0.25698324 0.03351955 0.09497207
#> S2 0.35585586 0.19369369 0.29279279 0.09909910 0.05855856
#> S3 0.34222222 0.03111111 0.11111111 0.08444444 0.43111111
#> S4 0.01886792 0.30188679 0.34905660 0.01886792 0.31132075
#> S5 0.23484848 0.20075758 0.03030303 0.24242424 0.29166667
#> S6 0.19642857 0.25000000 0.11785714 0.14285714 0.29285714