The formatters
package provides two core pieces of functionality, both
related to ASCII rendering:
format_value
provides the ability to format single- and
multi-valued elements into ASCII display-ready stringsmatrix_form
framework provides generics for implementing ASCII
rendering support for display tablesBoth of these feature sets are used in the rtables
package.
The core motivation for formatters
is the rendering of reporting
tables into ASCII. In this context a "value" is the raw content that to
appear in a single table cell. Most commonly this is a numeric vector of
length 1, 2 or β occasionally β 3.
formatters
is available on CRAN and you can install the latest released
version with:
install.packages("formatters")
or you can install the latest development version directly from GitHub with:
remotes::install_github("insightsengineering/formatters")
Note that you might need to set your GITHUB_PAT
environment variable in
order to be able to install from GitHub.
Packaged releases (both those on CRAN and those between official CRAN releases) can be found in the releases list.
formatters
ships with a large number of pre-defined formats
appropriate for rendering values into ASCII strings. These existing
formats are specified by their labels. We can see the list of these by
calling the list_valid_format_labels
function:
list_valid_format_labels()
$`1d`
[1] "xx" "xx." "xx.x"
[4] "xx.xx" "xx.xxx" "xx.xxxx"
[7] "xx%" "xx.%" "xx.x%"
[10] "xx.xx%" "xx.xxx%" "(N=xx)"
[13] ">999.9" ">999.99" "x.xxxx | (<0.0001)"
$`2d`
[1] "xx / xx" "xx. / xx." "xx.x / xx.x"
[4] "xx.xx / xx.xx" "xx.xxx / xx.xxx" "xx (xx%)"
[7] "xx (xx.%)" "xx (xx.x%)" "xx (xx.xx%)"
[10] "xx. (xx.%)" "xx.x (xx.x%)" "xx.xx (xx.xx%)"
[13] "(xx, xx)" "(xx., xx.)" "(xx.x, xx.x)"
[16] "(xx.xx, xx.xx)" "(xx.xxx, xx.xxx)" "(xx.xxxx, xx.xxxx)"
[19] "xx - xx" "xx.x - xx.x" "xx.xx - xx.xx"
[22] "xx (xx)" "xx. (xx.)" "xx.x (xx.x)"
[25] "xx.xx (xx.xx)" "xx (xx.)" "xx (xx.x)"
[28] "xx (xx.xx)" "xx.x, xx.x" "xx.x to xx.x"
$`3d`
[1] "xx.xx (xx.xx - xx.xx)"
attr(,"info")
[1] "xx does not modify the element, and xx. rounds a number to 0 digits"
Each of these labels describes how the incoming (possibly
multi-element) raw value will be formatted. xx
indicates that an
element of the value will be printed as is, with no modification. xx.
indicates that a numeric value element will be rounded to 0 decimal
places, xx.x
indicates rounding to 1 decimal place, etc.
Values are formatted via calls to format_value
, like so:
format_value(5.1235, format = "xx.xx")
[1] "5.12"
format_value(c(1.2355, 2.6789), "(xx.xx, xx.xx)")
[1] "(1.24, 2.68)"
Advanced Usage Only These features are supported, and in fact are
used in rtables
and the experimental rlistings
. That said, the API
is currently very low-level and tailored to what rtables
and
rlistings
need. How useful this is to other table frameworks may vary.
The second major piece of functionality in formatters
is the ability
to render tables into ASCII (and thus directly to the terminal) based on
a so-called MatrixPrintForm
representation of the table.
To hook up rtables
-style ASCII display for your tables, it suffices to
export a method for the exported matrix_form
generic formatters
provides. This method must return a MatrixPrintForm
object
representing your table.
We can build a baby example method for data.frames
to illustrate this
process:
## pagdfrow supports a large number of pieces of information regarding
## siblings and what information should be repeated after a pagination.
## we ignore all that here and just give the absolutely crucial info:
## nm (name), lab (label), rnum (absolute row position), pth ("path"),
## extent (how many lines it takes up), rclass ("class of row")
fake_pagdf_row <- function(i, rnms) {
nm <- rnms[i]
pagdfrow(nm = nm, lab = nm, rnum = i, pth = nm, extent = 1L,
rclass = "NA")
}
matrix_form.data.frame <- function(df) {
fmts <- lapply(df, function(x) if(is.null(obj_format(x))) "xx" else obj_format(x))
bodystrs <- mapply(function(x, fmt) {
sapply(x, format_value, format = fmt)
}, x = df, fmt = fmts)
rnms <- row.names(df)
if(is.null(rnms))
rnms <- as.character(seq_len(NROW(df)))
cnms <- names(df)
strings <- rbind(c("", cnms),
cbind(rnms, bodystrs))
fnr <- nrow(strings)
fnc <- ncol(strings)
## center alignment for column labels, left alignment for everything else
aligns <- rbind("center",
matrix("left", nrow = NROW(df), ncol = fnc))
## build up fake pagination df,
rowdf <- basic_pagdf(row.names(df))
MatrixPrintForm(strings = strings,
aligns = aligns,
spans = matrix(1, nrow = fnr, ncol = fnc),
formats = NULL,
row_info = rowdf,
has_topleft = FALSE,
nlines_header = 1,
nrow_header = 1)
}
cat(toString(matrix_form.data.frame(mtcars)))
mpg cyl disp hp drat wt qsec vs am gear carb
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Mazda RX4 21 6 160 110 3.9 2.62 16.46 0 1 4 4
Mazda RX4 Wag 21 6 160 110 3.9 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.32 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.44 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.46 20.22 1 0 3 1
Duster 360 14.3 8 360 245 3.21 3.57 15.84 0 0 3 4
Merc 240D 24.4 4 146.7 62 3.69 3.19 20 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.15 22.9 1 0 4 2
Merc 280 19.2 6 167.6 123 3.92 3.44 18.3 1 0 4 4
Merc 280C 17.8 6 167.6 123 3.92 3.44 18.9 1 0 4 4
Merc 450SE 16.4 8 275.8 180 3.07 4.07 17.4 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.73 17.6 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.78 18 0 0 3 3
Cadillac Fleetwood 10.4 8 472 205 2.93 5.25 17.98 0 0 3 4
Lincoln Continental 10.4 8 460 215 3 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440 230 3.23 5.345 17.42 0 0 3 4
Fiat 128 32.4 4 78.7 66 4.08 2.2 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.9 1 1 4 1
Toyota Corona 21.5 4 120.1 97 3.7 2.465 20.01 1 0 3 1
Dodge Challenger 15.5 8 318 150 2.76 3.52 16.87 0 0 3 2
AMC Javelin 15.2 8 304 150 3.15 3.435 17.3 0 0 3 2
Camaro Z28 13.3 8 350 245 3.73 3.84 15.41 0 0 3 4
Pontiac Firebird 19.2 8 400 175 3.08 3.845 17.05 0 0 3 2
Fiat X1-9 27.3 4 79 66 4.08 1.935 18.9 1 1 4 1
Porsche 914-2 26 4 120.3 91 4.43 2.14 16.7 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.9 1 1 5 2
Ford Pantera L 15.8 8 351 264 4.22 3.17 14.5 0 1 5 4
Ferrari Dino 19.7 6 145 175 3.62 2.77 15.5 0 1 5 6
Maserati Bora 15 8 301 335 3.54 3.57 14.6 0 1 5 8
Volvo 142E 21.4 4 121 109 4.11 2.78 18.6 1 1 4 2