as_huxtable or as_hux converts an object to a huxtable.
Conversion methods exist for data frames and tibbles, tables,
ftables, matrices and (most) vectors.
as_huxtable(x, ...)
as_hux(x, ...)
# S3 method for default
as_huxtable(
x,
add_colnames = getOption("huxtable.add_colnames", TRUE),
add_rownames = FALSE,
autoformat = getOption("huxtable.autoformat", TRUE),
...
)
# S3 method for grouped_df
as_huxtable(x, ..., groups_to_headers = FALSE)
is_huxtable(x)
is_hux(x)Object to convert.
Arguments passed on to huxtable().
If TRUE, add a first row of column names to the huxtable.
If TRUE or a character string, add a first column of row names
to the huxtable. The string gives the name for the new column (or "rownames" for TRUE).
If TRUE, automatically format columns by type. See below.
Logical. Convert groups to header rows?
An object of class "huxtable".
is_hux[table] tests if an object is a huxtable.
For table objects, add_colnames and add_rownames are TRUE by default. For
matrix objects, they are FALSE. Other classes use
options("huxtable.add_colnames"), which is TRUE by default; add_rownames
is FALSE.
For dplyr::grouped_df() objects, groups will be converted to header rows
if groups_to_headers is TRUE.
dfr <- data.frame(
a = 1:5,
b = letters[1:5],
stringsAsFactors = FALSE
)
as_huxtable(dfr)
#> a b
#> 1 a
#> 2 b
#> 3 c
#> 4 d
#> 5 e
#>
#> Column names: a, b
mx <- matrix(letters[1:12], 4, 3)
as_huxtable(mx, add_colnames = FALSE)
#> a e i
#> b f j
#> c g k
#> d h l
#>
#> Column names: V1, V2, V3
library(stats)
tbl <- table(
Wool = warpbreaks$wool,
Tension = warpbreaks$tension
)
as_huxtable(tbl) # adds row and column names by default
#> L M H
#> A 9 9 9
#> B 9 9 9
#>
#> Column names: rownames, L, M, H
# adding rownames:
as_hux(mtcars[1:3,], add_colnames = TRUE,
add_rownames = "Car")
#> Car mpg cyl disp hp drat wt
#> Mazda 21 6 160 110 3.9 2.62
#> RX4
#> Mazda 21 6 160 110 3.9 2.88
#> RX4 Wag
#> Datsun 22.8 4 108 93 3.85 2.32
#> 710
#>
#> Column names: Car, mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb
#>
#> 7/12 columns shown.
if (requireNamespace("dplyr")) {
iris_grp <- dplyr::group_by(iris[c(1:4, 51:54, 101:104), ], Species)
as_hux(iris_grp, groups_to_headers = TRUE)
}
#> Sepal.Length Sepal.Width Petal.Length Petal.Width
#> Species: setosa
#> 5.1 3.5 1.4 0.2
#> 4.9 3 1.4 0.2
#> 4.7 3.2 1.3 0.2
#> 4.6 3.1 1.5 0.2
#> Species: versicolor
#> 7 3.2 4.7 1.4
#> 6.4 3.2 4.5 1.5
#> 6.9 3.1 4.9 1.5
#> 5.5 2.3 4 1.3
#> Species: virginica
#> 6.3 3.3 6 2.5
#> 5.8 2.7 5.1 1.9
#> 7.1 3 5.9 2.1
#> 6.3 2.9 5.6 1.8
#>
#> Column names: Sepal.Length, Sepal.Width, Petal.Length, Petal.Width