Creates a Pandoc's markdown style table with optional caption and some other tweaks. See 'Details' below.
pandoc.table.return(
t,
caption,
digits = panderOptions("digits"),
decimal.mark = panderOptions("decimal.mark"),
big.mark = panderOptions("big.mark"),
round = panderOptions("round"),
missing = panderOptions("missing"),
justify,
style = c("multiline", "grid", "simple", "rmarkdown", "jira"),
split.tables = panderOptions("table.split.table"),
split.cells = panderOptions("table.split.cells"),
keep.trailing.zeros = panderOptions("keep.trailing.zeros"),
keep.line.breaks = panderOptions("keep.line.breaks"),
plain.ascii = panderOptions("plain.ascii"),
use.hyphening = panderOptions("use.hyphening"),
row.names,
col.names,
emphasize.rownames = panderOptions("table.emphasize.rownames"),
emphasize.rows,
emphasize.cols,
emphasize.cells,
emphasize.strong.rows,
emphasize.strong.cols,
emphasize.strong.cells,
emphasize.italics.rows,
emphasize.italics.cols,
emphasize.italics.cells,
emphasize.verbatim.rows,
emphasize.verbatim.cols,
emphasize.verbatim.cells,
...
)data frame, matrix or table
caption (string) to be shown under the table
passed to format. Can be a vector specifying values for each column (has to be the same length as number of columns).
passed to format
passed to format
passed to round. Can be a vector specifying values for each column (has to be the same length as number of columns). Values for non-numeric columns will be disregarded.
string to replace missing values
defines alignment in cells passed to format. Can be left, right or centre, which latter can be also spelled as center. Defaults to centre. Can be abbreviated to a string consisting of the letters l, c and r (e.g. 'lcr' instead of c('left', 'centre', 'right').
which Pandoc style to use: simple, multiline, grid or rmarkdown
where to split wide tables to separate tables. The default value (80) suggests the conventional number of characters used in a line, feel free to change (e.g. to Inf to disable this feature) if you are not using a VT100 terminal any more :)
where to split cells' text with line breaks. Default to 30, to disable set to Inf. Can be also supplied as a vector, for each cell separately (if length(split.cells) == number of columns + 1, then first value in split.cells if for row names, and others are for columns). Supports relative (percentage) parameters in combination with split.tables.
to show or remove trailing zeros in numbers on a column basis width
(default: FALSE) if to keep or remove line breaks from cells in a table
(default: FALSE) if output should be in plain ascii (without markdown markup) or not
boolean (default: FALSE) if try to use hyphening when splitting large cells according to table.split.cells. Requires sylly.
if FALSE, row names are suppressed. A character vector of row names can also be specified here. By default, row names are included if rownames(t) is neither
NULL nor identical to 1:nrow(x)
a character vector of column names to be used in the table
boolean (default: TRUE) if row names should be highlighted
deprecated for emphasize.italics.rows argument
deprecated for emphasize.italics.cols argument
deprecated for emphasize.italics.cells argument
see emphasize.italics.rows but in bold
see emphasize.italics.cols but in bold
see emphasize.italics.cells but in bold
a vector for a two dimensional table specifying which rows to emphasize
a vector for a two dimensional table specifying which cols to emphasize
a vector for one-dimensional tables or a matrix like structure with two columns for row and column indexes to be emphasized in two dimensional tables. See e.g. which(..., arr.ind = TRUE)
see emphasize.italics.rows but in verbatim
see emphasize.italics.cols but in verbatim
see emphasize.italics.cells but in verbatim
unsupported extra arguments directly placed into /dev/null
By default this function outputs (see: cat) the result. If you would want to catch the result instead, then call pandoc.table.return instead.
This function takes any tabular data as its first argument and will try to make it pretty like: rounding and applying digits and custom decimal.mark to numbers, auto-recognizing if row names should be included, setting alignment of cells and dropping trailing zeros by default.
pandoc.table also tries to split large cells with line breaks or even the whole table to separate parts on demand. Other arguments lets the use to highlight some rows/cells/cells in the table with italic or bold text style.
For more details please see the parameters above and passed arguments of panderOptions.
If caption is missing, then the value is first checked in t object's caption attribute and if not found in an internal buffer set by link{set.caption}. justify parameter works similarly, see set.alignment for details.
John MacFarlane (2012): _Pandoc User's Guide_. https://johnmacfarlane.net/pandoc/README.html
pandoc.table(mtcars)
#>
#> --------------------------------------------------------------------------------
#> mpg cyl disp hp drat wt qsec vs
#> ------------------------- ------ ----- ------- ----- ------ ------- ------- ----
#> **Mazda RX4** 21 6 160 110 3.9 2.62 16.46 0
#>
#> **Mazda RX4 Wag** 21 6 160 110 3.9 2.875 17.02 0
#>
#> **Datsun 710** 22.8 4 108 93 3.85 2.32 18.61 1
#>
#> **Hornet 4 Drive** 21.4 6 258 110 3.08 3.215 19.44 1
#>
#> **Hornet Sportabout** 18.7 8 360 175 3.15 3.44 17.02 0
#>
#> **Valiant** 18.1 6 225 105 2.76 3.46 20.22 1
#>
#> **Duster 360** 14.3 8 360 245 3.21 3.57 15.84 0
#>
#> **Merc 240D** 24.4 4 146.7 62 3.69 3.19 20 1
#>
#> **Merc 230** 22.8 4 140.8 95 3.92 3.15 22.9 1
#>
#> **Merc 280** 19.2 6 167.6 123 3.92 3.44 18.3 1
#>
#> **Merc 280C** 17.8 6 167.6 123 3.92 3.44 18.9 1
#>
#> **Merc 450SE** 16.4 8 275.8 180 3.07 4.07 17.4 0
#>
#> **Merc 450SL** 17.3 8 275.8 180 3.07 3.73 17.6 0
#>
#> **Merc 450SLC** 15.2 8 275.8 180 3.07 3.78 18 0
#>
#> **Cadillac Fleetwood** 10.4 8 472 205 2.93 5.25 17.98 0
#>
#> **Lincoln Continental** 10.4 8 460 215 3 5.424 17.82 0
#>
#> **Chrysler Imperial** 14.7 8 440 230 3.23 5.345 17.42 0
#>
#> **Fiat 128** 32.4 4 78.7 66 4.08 2.2 19.47 1
#>
#> **Honda Civic** 30.4 4 75.7 52 4.93 1.615 18.52 1
#>
#> **Toyota Corolla** 33.9 4 71.1 65 4.22 1.835 19.9 1
#>
#> **Toyota Corona** 21.5 4 120.1 97 3.7 2.465 20.01 1
#>
#> **Dodge Challenger** 15.5 8 318 150 2.76 3.52 16.87 0
#>
#> **AMC Javelin** 15.2 8 304 150 3.15 3.435 17.3 0
#>
#> **Camaro Z28** 13.3 8 350 245 3.73 3.84 15.41 0
#>
#> **Pontiac Firebird** 19.2 8 400 175 3.08 3.845 17.05 0
#>
#> **Fiat X1-9** 27.3 4 79 66 4.08 1.935 18.9 1
#>
#> **Porsche 914-2** 26 4 120.3 91 4.43 2.14 16.7 0
#>
#> **Lotus Europa** 30.4 4 95.1 113 3.77 1.513 16.9 1
#>
#> **Ford Pantera L** 15.8 8 351 264 4.22 3.17 14.5 0
#>
#> **Ferrari Dino** 19.7 6 145 175 3.62 2.77 15.5 0
#>
#> **Maserati Bora** 15 8 301 335 3.54 3.57 14.6 0
#>
#> **Volvo 142E** 21.4 4 121 109 4.11 2.78 18.6 1
#> --------------------------------------------------------------------------------
#>
#> Table: Table continues below
#>
#>
#> --------------------------------------------
#> am gear carb
#> ------------------------- ---- ------ ------
#> **Mazda RX4** 1 4 4
#>
#> **Mazda RX4 Wag** 1 4 4
#>
#> **Datsun 710** 1 4 1
#>
#> **Hornet 4 Drive** 0 3 1
#>
#> **Hornet Sportabout** 0 3 2
#>
#> **Valiant** 0 3 1
#>
#> **Duster 360** 0 3 4
#>
#> **Merc 240D** 0 4 2
#>
#> **Merc 230** 0 4 2
#>
#> **Merc 280** 0 4 4
#>
#> **Merc 280C** 0 4 4
#>
#> **Merc 450SE** 0 3 3
#>
#> **Merc 450SL** 0 3 3
#>
#> **Merc 450SLC** 0 3 3
#>
#> **Cadillac Fleetwood** 0 3 4
#>
#> **Lincoln Continental** 0 3 4
#>
#> **Chrysler Imperial** 0 3 4
#>
#> **Fiat 128** 1 4 1
#>
#> **Honda Civic** 1 4 2
#>
#> **Toyota Corolla** 1 4 1
#>
#> **Toyota Corona** 0 3 1
#>
#> **Dodge Challenger** 0 3 2
#>
#> **AMC Javelin** 0 3 2
#>
#> **Camaro Z28** 0 3 4
#>
#> **Pontiac Firebird** 0 3 2
#>
#> **Fiat X1-9** 1 4 1
#>
#> **Porsche 914-2** 1 5 2
#>
#> **Lotus Europa** 1 5 2
#>
#> **Ford Pantera L** 1 5 4
#>
#> **Ferrari Dino** 1 5 6
#>
#> **Maserati Bora** 1 5 8
#>
#> **Volvo 142E** 1 4 2
#> --------------------------------------------
#>
# caption
pandoc.table(mtcars, 'Motor Trend Car Road Tests')
#>
#> --------------------------------------------------------------------------------
#> mpg cyl disp hp drat wt qsec vs
#> ------------------------- ------ ----- ------- ----- ------ ------- ------- ----
#> **Mazda RX4** 21 6 160 110 3.9 2.62 16.46 0
#>
#> **Mazda RX4 Wag** 21 6 160 110 3.9 2.875 17.02 0
#>
#> **Datsun 710** 22.8 4 108 93 3.85 2.32 18.61 1
#>
#> **Hornet 4 Drive** 21.4 6 258 110 3.08 3.215 19.44 1
#>
#> **Hornet Sportabout** 18.7 8 360 175 3.15 3.44 17.02 0
#>
#> **Valiant** 18.1 6 225 105 2.76 3.46 20.22 1
#>
#> **Duster 360** 14.3 8 360 245 3.21 3.57 15.84 0
#>
#> **Merc 240D** 24.4 4 146.7 62 3.69 3.19 20 1
#>
#> **Merc 230** 22.8 4 140.8 95 3.92 3.15 22.9 1
#>
#> **Merc 280** 19.2 6 167.6 123 3.92 3.44 18.3 1
#>
#> **Merc 280C** 17.8 6 167.6 123 3.92 3.44 18.9 1
#>
#> **Merc 450SE** 16.4 8 275.8 180 3.07 4.07 17.4 0
#>
#> **Merc 450SL** 17.3 8 275.8 180 3.07 3.73 17.6 0
#>
#> **Merc 450SLC** 15.2 8 275.8 180 3.07 3.78 18 0
#>
#> **Cadillac Fleetwood** 10.4 8 472 205 2.93 5.25 17.98 0
#>
#> **Lincoln Continental** 10.4 8 460 215 3 5.424 17.82 0
#>
#> **Chrysler Imperial** 14.7 8 440 230 3.23 5.345 17.42 0
#>
#> **Fiat 128** 32.4 4 78.7 66 4.08 2.2 19.47 1
#>
#> **Honda Civic** 30.4 4 75.7 52 4.93 1.615 18.52 1
#>
#> **Toyota Corolla** 33.9 4 71.1 65 4.22 1.835 19.9 1
#>
#> **Toyota Corona** 21.5 4 120.1 97 3.7 2.465 20.01 1
#>
#> **Dodge Challenger** 15.5 8 318 150 2.76 3.52 16.87 0
#>
#> **AMC Javelin** 15.2 8 304 150 3.15 3.435 17.3 0
#>
#> **Camaro Z28** 13.3 8 350 245 3.73 3.84 15.41 0
#>
#> **Pontiac Firebird** 19.2 8 400 175 3.08 3.845 17.05 0
#>
#> **Fiat X1-9** 27.3 4 79 66 4.08 1.935 18.9 1
#>
#> **Porsche 914-2** 26 4 120.3 91 4.43 2.14 16.7 0
#>
#> **Lotus Europa** 30.4 4 95.1 113 3.77 1.513 16.9 1
#>
#> **Ford Pantera L** 15.8 8 351 264 4.22 3.17 14.5 0
#>
#> **Ferrari Dino** 19.7 6 145 175 3.62 2.77 15.5 0
#>
#> **Maserati Bora** 15 8 301 335 3.54 3.57 14.6 0
#>
#> **Volvo 142E** 21.4 4 121 109 4.11 2.78 18.6 1
#> --------------------------------------------------------------------------------
#>
#> Table: Motor Trend Car Road Tests (continued below)
#>
#>
#> --------------------------------------------
#> am gear carb
#> ------------------------- ---- ------ ------
#> **Mazda RX4** 1 4 4
#>
#> **Mazda RX4 Wag** 1 4 4
#>
#> **Datsun 710** 1 4 1
#>
#> **Hornet 4 Drive** 0 3 1
#>
#> **Hornet Sportabout** 0 3 2
#>
#> **Valiant** 0 3 1
#>
#> **Duster 360** 0 3 4
#>
#> **Merc 240D** 0 4 2
#>
#> **Merc 230** 0 4 2
#>
#> **Merc 280** 0 4 4
#>
#> **Merc 280C** 0 4 4
#>
#> **Merc 450SE** 0 3 3
#>
#> **Merc 450SL** 0 3 3
#>
#> **Merc 450SLC** 0 3 3
#>
#> **Cadillac Fleetwood** 0 3 4
#>
#> **Lincoln Continental** 0 3 4
#>
#> **Chrysler Imperial** 0 3 4
#>
#> **Fiat 128** 1 4 1
#>
#> **Honda Civic** 1 4 2
#>
#> **Toyota Corolla** 1 4 1
#>
#> **Toyota Corona** 0 3 1
#>
#> **Dodge Challenger** 0 3 2
#>
#> **AMC Javelin** 0 3 2
#>
#> **Camaro Z28** 0 3 4
#>
#> **Pontiac Firebird** 0 3 2
#>
#> **Fiat X1-9** 1 4 1
#>
#> **Porsche 914-2** 1 5 2
#>
#> **Lotus Europa** 1 5 2
#>
#> **Ford Pantera L** 1 5 4
#>
#> **Ferrari Dino** 1 5 6
#>
#> **Maserati Bora** 1 5 8
#>
#> **Volvo 142E** 1 4 2
#> --------------------------------------------
#>
# other input/output formats
pandoc.table(mtcars[, 1:3], decimal.mark = ',')
#>
#> ----------------------------------------------
#> mpg cyl disp
#> ------------------------- ------ ----- -------
#> **Mazda RX4** 21 6 160
#>
#> **Mazda RX4 Wag** 21 6 160
#>
#> **Datsun 710** 22,8 4 108
#>
#> **Hornet 4 Drive** 21,4 6 258
#>
#> **Hornet Sportabout** 18,7 8 360
#>
#> **Valiant** 18,1 6 225
#>
#> **Duster 360** 14,3 8 360
#>
#> **Merc 240D** 24,4 4 146,7
#>
#> **Merc 230** 22,8 4 140,8
#>
#> **Merc 280** 19,2 6 167,6
#>
#> **Merc 280C** 17,8 6 167,6
#>
#> **Merc 450SE** 16,4 8 275,8
#>
#> **Merc 450SL** 17,3 8 275,8
#>
#> **Merc 450SLC** 15,2 8 275,8
#>
#> **Cadillac Fleetwood** 10,4 8 472
#>
#> **Lincoln Continental** 10,4 8 460
#>
#> **Chrysler Imperial** 14,7 8 440
#>
#> **Fiat 128** 32,4 4 78,7
#>
#> **Honda Civic** 30,4 4 75,7
#>
#> **Toyota Corolla** 33,9 4 71,1
#>
#> **Toyota Corona** 21,5 4 120,1
#>
#> **Dodge Challenger** 15,5 8 318
#>
#> **AMC Javelin** 15,2 8 304
#>
#> **Camaro Z28** 13,3 8 350
#>
#> **Pontiac Firebird** 19,2 8 400
#>
#> **Fiat X1-9** 27,3 4 79
#>
#> **Porsche 914-2** 26 4 120,3
#>
#> **Lotus Europa** 30,4 4 95,1
#>
#> **Ford Pantera L** 15,8 8 351
#>
#> **Ferrari Dino** 19,7 6 145
#>
#> **Maserati Bora** 15 8 301
#>
#> **Volvo 142E** 21,4 4 121
#> ----------------------------------------------
#>
pandoc.table(mtcars[, 1:3], decimal.mark = ',', justify = 'right')
#>
#> ----------------------------------------------
#> mpg cyl disp
#> ------------------------- ------ ----- -------
#> **Mazda RX4** 21 6 160
#>
#> **Mazda RX4 Wag** 21 6 160
#>
#> **Datsun 710** 22,8 4 108
#>
#> **Hornet 4 Drive** 21,4 6 258
#>
#> **Hornet Sportabout** 18,7 8 360
#>
#> **Valiant** 18,1 6 225
#>
#> **Duster 360** 14,3 8 360
#>
#> **Merc 240D** 24,4 4 146,7
#>
#> **Merc 230** 22,8 4 140,8
#>
#> **Merc 280** 19,2 6 167,6
#>
#> **Merc 280C** 17,8 6 167,6
#>
#> **Merc 450SE** 16,4 8 275,8
#>
#> **Merc 450SL** 17,3 8 275,8
#>
#> **Merc 450SLC** 15,2 8 275,8
#>
#> **Cadillac Fleetwood** 10,4 8 472
#>
#> **Lincoln Continental** 10,4 8 460
#>
#> **Chrysler Imperial** 14,7 8 440
#>
#> **Fiat 128** 32,4 4 78,7
#>
#> **Honda Civic** 30,4 4 75,7
#>
#> **Toyota Corolla** 33,9 4 71,1
#>
#> **Toyota Corona** 21,5 4 120,1
#>
#> **Dodge Challenger** 15,5 8 318
#>
#> **AMC Javelin** 15,2 8 304
#>
#> **Camaro Z28** 13,3 8 350
#>
#> **Pontiac Firebird** 19,2 8 400
#>
#> **Fiat X1-9** 27,3 4 79
#>
#> **Porsche 914-2** 26 4 120,3
#>
#> **Lotus Europa** 30,4 4 95,1
#>
#> **Ford Pantera L** 15,8 8 351
#>
#> **Ferrari Dino** 19,7 6 145
#>
#> **Maserati Bora** 15 8 301
#>
#> **Volvo 142E** 21,4 4 121
#> ----------------------------------------------
#>
pandoc.table(matrix(sample(1:1000, 25), 5, 5))
#>
#> ----- ----- ----- ----- -----
#> 384 432 515 268 758
#>
#> 145 807 775 295 113
#>
#> 714 213 689 395 492
#>
#> 748 484 198 42 244
#>
#> 269 705 475 40 527
#> ----- ----- ----- ----- -----
#>
pandoc.table(matrix(runif(25), 5, 5))
#>
#> --------- -------- -------- -------- ---------
#> 0.08522 0.4848 0.3219 0.9061 0.9473
#>
#> 0.8561 0.2472 0.3615 0.7727 0.2161
#>
#> 0.07698 0.6866 0.8877 0.3834 0.03209
#>
#> 0.8528 0.1636 0.828 0.9997 0.1453
#>
#> 0.1063 0.9528 0.1007 0.3493 0.8544
#> --------- -------- -------- -------- ---------
#>
pandoc.table(matrix(runif(25), 5, 5), digits = 5)
#>
#> ---------- --------- --------- ---------- ---------
#> 0.21315 0.78112 0.58984 0.13807 0.32932
#>
#> 0.21031 0.28824 0.75916 0.080845 0.97947
#>
#> 0.039521 0.87536 0.83608 0.65598 0.71519
#>
#> 0.94477 0.29575 0.76282 0.602 0.87263
#>
#> 0.24493 0.98353 0.41727 0.657 0.98328
#> ---------- --------- --------- ---------- ---------
#>
pandoc.table(matrix(runif(25),5,5), round = 1)
#>
#> ----- ----- ----- ----- -----
#> 0.2 0.6 0 0.7 0.4
#>
#> 0.7 0.4 0.7 0.8 0.7
#>
#> 0.4 0.9 0.4 0.5 0.6
#>
#> 0 0.5 0.9 0.2 0.4
#>
#> 0.6 1 0.7 0.5 1
#> ----- ----- ----- ----- -----
#>
pandoc.table(table(mtcars$am))
#>
#> ---------
#> 0 1
#> ---- ----
#> 19 13
#> ---------
#>
pandoc.table(table(mtcars$am, mtcars$gear))
#>
#> ---------------------
#> 3 4 5
#> -------- ---- --- ---
#> **0** 15 4 0
#>
#> **1** 0 8 5
#> ---------------------
#>
pandoc.table(table(state.division, state.region))
#>
#> -------------------------------------------------------------------
#> Northeast South North Central West
#> ------------------------ ----------- ------- --------------- ------
#> **New England** 6 0 0 0
#>
#> **Middle Atlantic** 3 0 0 0
#>
#> **South Atlantic** 0 8 0 0
#>
#> **East South Central** 0 4 0 0
#>
#> **West South Central** 0 4 0 0
#>
#> **East North Central** 0 0 5 0
#>
#> **West North Central** 0 0 7 0
#>
#> **Mountain** 0 0 0 8
#>
#> **Pacific** 0 0 0 5
#> -------------------------------------------------------------------
#>
pandoc.table(table(state.division, state.region), justify = 'centre')
#>
#> -------------------------------------------------------------------
#> Northeast South North Central West
#> ------------------------ ----------- ------- --------------- ------
#> **New England** 6 0 0 0
#>
#> **Middle Atlantic** 3 0 0 0
#>
#> **South Atlantic** 0 8 0 0
#>
#> **East South Central** 0 4 0 0
#>
#> **West South Central** 0 4 0 0
#>
#> **East North Central** 0 0 5 0
#>
#> **West North Central** 0 0 7 0
#>
#> **Mountain** 0 0 0 8
#>
#> **Pacific** 0 0 0 5
#> -------------------------------------------------------------------
#>
m <- data.frame(a = c(1, -500, 10320, 23, 77),
b = runif(5),
c = c('a', 'bb', 'ccc', 'dddd', 'eeeee'))
pandoc.table(m)
#>
#> ------------------------
#> a b c
#> ------- -------- -------
#> 1 0.2987 a
#>
#> -500 0.0502 bb
#>
#> 10320 0.5762 ccc
#>
#> 23 0.2179 dddd
#>
#> 77 0.1259 eeeee
#> ------------------------
#>
pandoc.table(m, justify = c('right', 'left', 'centre'))
#>
#> ------------------------
#> a b c
#> ------- -------- -------
#> 1 0.2987 a
#>
#> -500 0.0502 bb
#>
#> 10320 0.5762 ccc
#>
#> 23 0.2179 dddd
#>
#> 77 0.1259 eeeee
#> ------------------------
#>
pandoc.table(m, justify = 'rlc') # Same as upper statement
#>
#> ------------------------
#> a b c
#> ------- -------- -------
#> 1 0.2987 a
#>
#> -500 0.0502 bb
#>
#> 10320 0.5762 ccc
#>
#> 23 0.2179 dddd
#>
#> 77 0.1259 eeeee
#> ------------------------
#>
## splitting up too wide tables
pandoc.table(mtcars)
#>
#> --------------------------------------------------------------------------------
#> mpg cyl disp hp drat wt qsec vs
#> ------------------------- ------ ----- ------- ----- ------ ------- ------- ----
#> **Mazda RX4** 21 6 160 110 3.9 2.62 16.46 0
#>
#> **Mazda RX4 Wag** 21 6 160 110 3.9 2.875 17.02 0
#>
#> **Datsun 710** 22.8 4 108 93 3.85 2.32 18.61 1
#>
#> **Hornet 4 Drive** 21.4 6 258 110 3.08 3.215 19.44 1
#>
#> **Hornet Sportabout** 18.7 8 360 175 3.15 3.44 17.02 0
#>
#> **Valiant** 18.1 6 225 105 2.76 3.46 20.22 1
#>
#> **Duster 360** 14.3 8 360 245 3.21 3.57 15.84 0
#>
#> **Merc 240D** 24.4 4 146.7 62 3.69 3.19 20 1
#>
#> **Merc 230** 22.8 4 140.8 95 3.92 3.15 22.9 1
#>
#> **Merc 280** 19.2 6 167.6 123 3.92 3.44 18.3 1
#>
#> **Merc 280C** 17.8 6 167.6 123 3.92 3.44 18.9 1
#>
#> **Merc 450SE** 16.4 8 275.8 180 3.07 4.07 17.4 0
#>
#> **Merc 450SL** 17.3 8 275.8 180 3.07 3.73 17.6 0
#>
#> **Merc 450SLC** 15.2 8 275.8 180 3.07 3.78 18 0
#>
#> **Cadillac Fleetwood** 10.4 8 472 205 2.93 5.25 17.98 0
#>
#> **Lincoln Continental** 10.4 8 460 215 3 5.424 17.82 0
#>
#> **Chrysler Imperial** 14.7 8 440 230 3.23 5.345 17.42 0
#>
#> **Fiat 128** 32.4 4 78.7 66 4.08 2.2 19.47 1
#>
#> **Honda Civic** 30.4 4 75.7 52 4.93 1.615 18.52 1
#>
#> **Toyota Corolla** 33.9 4 71.1 65 4.22 1.835 19.9 1
#>
#> **Toyota Corona** 21.5 4 120.1 97 3.7 2.465 20.01 1
#>
#> **Dodge Challenger** 15.5 8 318 150 2.76 3.52 16.87 0
#>
#> **AMC Javelin** 15.2 8 304 150 3.15 3.435 17.3 0
#>
#> **Camaro Z28** 13.3 8 350 245 3.73 3.84 15.41 0
#>
#> **Pontiac Firebird** 19.2 8 400 175 3.08 3.845 17.05 0
#>
#> **Fiat X1-9** 27.3 4 79 66 4.08 1.935 18.9 1
#>
#> **Porsche 914-2** 26 4 120.3 91 4.43 2.14 16.7 0
#>
#> **Lotus Europa** 30.4 4 95.1 113 3.77 1.513 16.9 1
#>
#> **Ford Pantera L** 15.8 8 351 264 4.22 3.17 14.5 0
#>
#> **Ferrari Dino** 19.7 6 145 175 3.62 2.77 15.5 0
#>
#> **Maserati Bora** 15 8 301 335 3.54 3.57 14.6 0
#>
#> **Volvo 142E** 21.4 4 121 109 4.11 2.78 18.6 1
#> --------------------------------------------------------------------------------
#>
#> Table: Table continues below
#>
#>
#> --------------------------------------------
#> am gear carb
#> ------------------------- ---- ------ ------
#> **Mazda RX4** 1 4 4
#>
#> **Mazda RX4 Wag** 1 4 4
#>
#> **Datsun 710** 1 4 1
#>
#> **Hornet 4 Drive** 0 3 1
#>
#> **Hornet Sportabout** 0 3 2
#>
#> **Valiant** 0 3 1
#>
#> **Duster 360** 0 3 4
#>
#> **Merc 240D** 0 4 2
#>
#> **Merc 230** 0 4 2
#>
#> **Merc 280** 0 4 4
#>
#> **Merc 280C** 0 4 4
#>
#> **Merc 450SE** 0 3 3
#>
#> **Merc 450SL** 0 3 3
#>
#> **Merc 450SLC** 0 3 3
#>
#> **Cadillac Fleetwood** 0 3 4
#>
#> **Lincoln Continental** 0 3 4
#>
#> **Chrysler Imperial** 0 3 4
#>
#> **Fiat 128** 1 4 1
#>
#> **Honda Civic** 1 4 2
#>
#> **Toyota Corolla** 1 4 1
#>
#> **Toyota Corona** 0 3 1
#>
#> **Dodge Challenger** 0 3 2
#>
#> **AMC Javelin** 0 3 2
#>
#> **Camaro Z28** 0 3 4
#>
#> **Pontiac Firebird** 0 3 2
#>
#> **Fiat X1-9** 1 4 1
#>
#> **Porsche 914-2** 1 5 2
#>
#> **Lotus Europa** 1 5 2
#>
#> **Ford Pantera L** 1 5 4
#>
#> **Ferrari Dino** 1 5 6
#>
#> **Maserati Bora** 1 5 8
#>
#> **Volvo 142E** 1 4 2
#> --------------------------------------------
#>
pandoc.table(mtcars, caption = 'Only once after the first part!')
#>
#> --------------------------------------------------------------------------------
#> mpg cyl disp hp drat wt qsec vs
#> ------------------------- ------ ----- ------- ----- ------ ------- ------- ----
#> **Mazda RX4** 21 6 160 110 3.9 2.62 16.46 0
#>
#> **Mazda RX4 Wag** 21 6 160 110 3.9 2.875 17.02 0
#>
#> **Datsun 710** 22.8 4 108 93 3.85 2.32 18.61 1
#>
#> **Hornet 4 Drive** 21.4 6 258 110 3.08 3.215 19.44 1
#>
#> **Hornet Sportabout** 18.7 8 360 175 3.15 3.44 17.02 0
#>
#> **Valiant** 18.1 6 225 105 2.76 3.46 20.22 1
#>
#> **Duster 360** 14.3 8 360 245 3.21 3.57 15.84 0
#>
#> **Merc 240D** 24.4 4 146.7 62 3.69 3.19 20 1
#>
#> **Merc 230** 22.8 4 140.8 95 3.92 3.15 22.9 1
#>
#> **Merc 280** 19.2 6 167.6 123 3.92 3.44 18.3 1
#>
#> **Merc 280C** 17.8 6 167.6 123 3.92 3.44 18.9 1
#>
#> **Merc 450SE** 16.4 8 275.8 180 3.07 4.07 17.4 0
#>
#> **Merc 450SL** 17.3 8 275.8 180 3.07 3.73 17.6 0
#>
#> **Merc 450SLC** 15.2 8 275.8 180 3.07 3.78 18 0
#>
#> **Cadillac Fleetwood** 10.4 8 472 205 2.93 5.25 17.98 0
#>
#> **Lincoln Continental** 10.4 8 460 215 3 5.424 17.82 0
#>
#> **Chrysler Imperial** 14.7 8 440 230 3.23 5.345 17.42 0
#>
#> **Fiat 128** 32.4 4 78.7 66 4.08 2.2 19.47 1
#>
#> **Honda Civic** 30.4 4 75.7 52 4.93 1.615 18.52 1
#>
#> **Toyota Corolla** 33.9 4 71.1 65 4.22 1.835 19.9 1
#>
#> **Toyota Corona** 21.5 4 120.1 97 3.7 2.465 20.01 1
#>
#> **Dodge Challenger** 15.5 8 318 150 2.76 3.52 16.87 0
#>
#> **AMC Javelin** 15.2 8 304 150 3.15 3.435 17.3 0
#>
#> **Camaro Z28** 13.3 8 350 245 3.73 3.84 15.41 0
#>
#> **Pontiac Firebird** 19.2 8 400 175 3.08 3.845 17.05 0
#>
#> **Fiat X1-9** 27.3 4 79 66 4.08 1.935 18.9 1
#>
#> **Porsche 914-2** 26 4 120.3 91 4.43 2.14 16.7 0
#>
#> **Lotus Europa** 30.4 4 95.1 113 3.77 1.513 16.9 1
#>
#> **Ford Pantera L** 15.8 8 351 264 4.22 3.17 14.5 0
#>
#> **Ferrari Dino** 19.7 6 145 175 3.62 2.77 15.5 0
#>
#> **Maserati Bora** 15 8 301 335 3.54 3.57 14.6 0
#>
#> **Volvo 142E** 21.4 4 121 109 4.11 2.78 18.6 1
#> --------------------------------------------------------------------------------
#>
#> Table: Only once after the first part! (continued below)
#>
#>
#> --------------------------------------------
#> am gear carb
#> ------------------------- ---- ------ ------
#> **Mazda RX4** 1 4 4
#>
#> **Mazda RX4 Wag** 1 4 4
#>
#> **Datsun 710** 1 4 1
#>
#> **Hornet 4 Drive** 0 3 1
#>
#> **Hornet Sportabout** 0 3 2
#>
#> **Valiant** 0 3 1
#>
#> **Duster 360** 0 3 4
#>
#> **Merc 240D** 0 4 2
#>
#> **Merc 230** 0 4 2
#>
#> **Merc 280** 0 4 4
#>
#> **Merc 280C** 0 4 4
#>
#> **Merc 450SE** 0 3 3
#>
#> **Merc 450SL** 0 3 3
#>
#> **Merc 450SLC** 0 3 3
#>
#> **Cadillac Fleetwood** 0 3 4
#>
#> **Lincoln Continental** 0 3 4
#>
#> **Chrysler Imperial** 0 3 4
#>
#> **Fiat 128** 1 4 1
#>
#> **Honda Civic** 1 4 2
#>
#> **Toyota Corolla** 1 4 1
#>
#> **Toyota Corona** 0 3 1
#>
#> **Dodge Challenger** 0 3 2
#>
#> **AMC Javelin** 0 3 2
#>
#> **Camaro Z28** 0 3 4
#>
#> **Pontiac Firebird** 0 3 2
#>
#> **Fiat X1-9** 1 4 1
#>
#> **Porsche 914-2** 1 5 2
#>
#> **Lotus Europa** 1 5 2
#>
#> **Ford Pantera L** 1 5 4
#>
#> **Ferrari Dino** 1 5 6
#>
#> **Maserati Bora** 1 5 8
#>
#> **Volvo 142E** 1 4 2
#> --------------------------------------------
#>
## tables with line breaks in cells
## NOTE: line breaks are removed from table content in case keep.line.breaks is set to FALSE
## and added automatically based on "split.cells" parameter!
t <- data.frame(a = c('hundreds\nof\nmouses', '3 cats'), b=c('FOO is nice', 'BAR\nBAR2'))
pandoc.table(t)
#>
#> ----------------------------------
#> a b
#> -------------------- -------------
#> hundreds of mouses FOO is nice
#>
#> 3 cats BAR BAR2
#> ----------------------------------
#>
pandoc.table(t, split.cells = 5)
#>
#> -----------------
#> a b
#> ---------- ------
#> hundreds FOO
#> of is
#> mouses nice
#>
#> 3 BAR
#> cats BAR2
#> -----------------
#>
## exporting tables in other Pandoc styles
pandoc.table(m)
#>
#> ------------------------
#> a b c
#> ------- -------- -------
#> 1 0.2987 a
#>
#> -500 0.0502 bb
#>
#> 10320 0.5762 ccc
#>
#> 23 0.2179 dddd
#>
#> 77 0.1259 eeeee
#> ------------------------
#>
pandoc.table(m, style = "grid")
#>
#>
#> +-------+--------+-------+
#> | a | b | c |
#> +=======+========+=======+
#> | 1 | 0.2987 | a |
#> +-------+--------+-------+
#> | -500 | 0.0502 | bb |
#> +-------+--------+-------+
#> | 10320 | 0.5762 | ccc |
#> +-------+--------+-------+
#> | 23 | 0.2179 | dddd |
#> +-------+--------+-------+
#> | 77 | 0.1259 | eeeee |
#> +-------+--------+-------+
#>
pandoc.table(m, style = "simple")
#>
#>
#> a b c
#> ------- -------- -------
#> 1 0.2987 a
#> -500 0.0502 bb
#> 10320 0.5762 ccc
#> 23 0.2179 dddd
#> 77 0.1259 eeeee
#>
pandoc.table(t, style = "grid")
#>
#>
#> +--------------------+-------------+
#> | a | b |
#> +====================+=============+
#> | hundreds of mouses | FOO is nice |
#> +--------------------+-------------+
#> | 3 cats | BAR BAR2 |
#> +--------------------+-------------+
#>
pandoc.table(t, style = "grid", split.cells = 5)
#>
#>
#> +----------+------+
#> | a | b |
#> +==========+======+
#> | hundreds | FOO |
#> | of | is |
#> | mouses | nice |
#> +----------+------+
#> | 3 | BAR |
#> | cats | BAR2 |
#> +----------+------+
#>
tryCatch(pandoc.table(t, style = "simple", split.cells = 5),
error = function(e) 'Yeah, no newline support in simple tables')
#> [1] "Yeah, no newline support in simple tables"
## highlight cells
t <- mtcars[1:3, 1:5]
pandoc.table(t$mpg, emphasize.italics.cells = 1)
#>
#> ------ ---- ------
#> *21* 21 22.8
#>
#> ------ ---- ------
#>
pandoc.table(t$mpg, emphasize.strong.cells = 1)
#>
#> -------- ---- ------
#> **21** 21 22.8
#>
#> -------- ---- ------
#>
pandoc.table(t$mpg, emphasize.italics.cells = 1, emphasize.strong.cells = 1)
#>
#> ---------- ---- ------
#> ***21*** 21 22.8
#>
#> ---------- ---- ------
#>
pandoc.table(t$mpg, emphasize.italics.cells = 1:2)
#>
#> ------ ------ ------
#> *21* *21* 22.8
#>
#> ------ ------ ------
#>
pandoc.table(t$mpg, emphasize.strong.cells = 1:2)
#>
#> -------- -------- ------
#> **21** **21** 22.8
#>
#> -------- -------- ------
#>
pandoc.table(t, emphasize.italics.cells = which(t > 20, arr.ind = TRUE))
#>
#> ---------------------------------------------------------
#> mpg cyl disp hp drat
#> ------------------- -------- ----- ------- ------- ------
#> **Mazda RX4** *21* 6 *160* *110* 3.9
#>
#> **Mazda RX4 Wag** *21* 6 *160* *110* 3.9
#>
#> **Datsun 710** *22.8* 4 *108* *93* 3.85
#> ---------------------------------------------------------
#>
pandoc.table(t, emphasize.italics.cells = which(t == 6, arr.ind = TRUE))
#>
#> ----------------------------------------------------
#> mpg cyl disp hp drat
#> ------------------- ------ ----- ------ ----- ------
#> **Mazda RX4** 21 *6* 160 110 3.9
#>
#> **Mazda RX4 Wag** 21 *6* 160 110 3.9
#>
#> **Datsun 710** 22.8 4 108 93 3.85
#> ----------------------------------------------------
#>
pandoc.table(t, emphasize.verbatim.cells = which(t == 6, arr.ind = TRUE))
#>
#> ----------------------------------------------------
#> mpg cyl disp hp drat
#> ------------------- ------ ----- ------ ----- ------
#> **Mazda RX4** 21 `6` 160 110 3.9
#>
#> **Mazda RX4 Wag** 21 `6` 160 110 3.9
#>
#> **Datsun 710** 22.8 4 108 93 3.85
#> ----------------------------------------------------
#>
pandoc.table(t, emphasize.verbatim.cells = which(t == 6, arr.ind = TRUE),
emphasize.italics.rows = 1)
#>
#> ----------------------------------------------------------
#> mpg cyl disp hp drat
#> ------------------- ------ ------- ------- ------- -------
#> **Mazda RX4** *21* *`6`* *160* *110* *3.9*
#>
#> **Mazda RX4 Wag** 21 `6` 160 110 3.9
#>
#> **Datsun 710** 22.8 4 108 93 3.85
#> ----------------------------------------------------------
#>
## with helpers
emphasize.cols(1)
emphasize.rows(1)
pandoc.table(t)
#>
#> ----------------------------------------------------------
#> mpg cyl disp hp drat
#> ------------------- -------- ----- ------- ------- -------
#> **Mazda RX4** *21* *6* *160* *110* *3.9*
#>
#> **Mazda RX4 Wag** *21* 6 160 110 3.9
#>
#> **Datsun 710** *22.8* 4 108 93 3.85
#> ----------------------------------------------------------
#>
emphasize.strong.cells(which(t > 20, arr.ind = TRUE))
pandoc.table(t)
#>
#> ---------------------------------------------------------------
#> mpg cyl disp hp drat
#> ------------------- ---------- ----- --------- --------- ------
#> **Mazda RX4** **21** 6 **160** **110** 3.9
#>
#> **Mazda RX4 Wag** **21** 6 **160** **110** 3.9
#>
#> **Datsun 710** **22.8** 4 **108** **93** 3.85
#> ---------------------------------------------------------------
#>
### plain.ascii
pandoc.table(mtcars[1:3, 1:3], plain.ascii = TRUE)
#>
#> ---------------------------------------
#> mpg cyl disp
#> ------------------- ------ ----- ------
#> Mazda RX4 21 6 160
#>
#> Mazda RX4 Wag 21 6 160
#>
#> Datsun 710 22.8 4 108
#> ---------------------------------------
#>
### keep.line.breaks
x <- data.frame(a="Pandoc\nPackage")
pandoc.table(x)
#>
#> ----------------
#> a
#> ----------------
#> Pandoc Package
#> ----------------
#>
pandoc.table(x, keep.line.breaks = TRUE)
#>
#> ---------
#> a
#> ---------
#> Pandoc
#> Package
#> ---------
#>
## split.cells
x <- data.frame(a = "foo bar", b = "foo bar")
pandoc.table(x, split.cells = 4)
#>
#> -----------
#> a b
#> ----- -----
#> foo foo
#> bar bar
#> -----------
#>
pandoc.table(x, split.cells = 7)
#>
#> -------------------
#> a b
#> --------- ---------
#> foo bar foo bar
#> -------------------
#>
pandoc.table(x, split.cells = c(4, 7))
#>
#> ---------------
#> a b
#> ----- ---------
#> foo foo bar
#> bar
#> ---------------
#>
pandoc.table(x, split.cells = c("20%", "80%"), split.tables = 30)
#>
#> ---------------
#> a b
#> ----- ---------
#> foo foo bar
#> bar
#> ---------------
#>
y <- c("aa aa aa", "aaa aaa", "a a a a a", "aaaaa", "bbbb bbbb bbbb", "bb bbb bbbb")
y <- matrix(y, ncol = 3, nrow = 2)
rownames(y) <- c("rowname one", "rowname two")
colnames(y) <- c("colname one", "colname two", "colname three")
pandoc.table(y, split.cells = 2)
#>
#> -----------------------------------------
#> colname colname colname
#> one two three
#> ----------- --------- --------- ---------
#> **rowname aa a bbbb
#> one** aa a bbbb
#> aa a bbbb
#> a
#> a
#>
#> **rowname aaa aaaaa bb
#> two** aaa bbb
#> bbbb
#> -----------------------------------------
#>
pandoc.table(y, split.cells = 6)
#>
#> -----------------------------------------
#> colname colname colname
#> one two three
#> ----------- --------- --------- ---------
#> **rowname aa aa a a a bbbb
#> one** aa a a bbbb
#> bbbb
#>
#> **rowname aaa aaaaa bb bbb
#> two** aaa bbbb
#> -----------------------------------------
#>
pandoc.table(y, split.cells = c(2, 6, 10))
#>
#> -------------------------------------------------
#> colname colname colname
#> one two three
#> ----------------- --------- --------- -----------
#> **rowname one** aa a a a bbbb bbbb
#> aa a a bbbb
#> aa
#>
#> **rowname two** aaa aaaaa bb bbb
#> aaa bbbb
#> -------------------------------------------------
#>
pandoc.table(y, split.cells = c(2, Inf, Inf))
#>
#> ----------------------------------------------------------
#> colname colname two colname three
#> one
#> ----------------- --------- ------------- ----------------
#> **rowname one** aa a a a a a bbbb bbbb bbbb
#> aa
#> aa
#>
#> **rowname two** aaa aaaaa bb bbb bbbb
#> aaa
#> ----------------------------------------------------------
#>
## first value used for rownames
pander(y, split.cells = c(5, 2, Inf, Inf))
#>
#> ----------------------------------------------------
#> colname colname two colname three
#> one
#> ----------- --------- ------------- ----------------
#> **rowname aa a a a a a bbbb bbbb bbbb
#> one** aa
#> aa
#>
#> **rowname aaa aaaaa bb bbb bbbb
#> two** aaa
#> ----------------------------------------------------
#>
pandoc.table(y, split.cells = c(5, 2, Inf, 5, 3, 10))
#>
#> ---------------------------------------------
#> colname colname two colname
#> one three
#> ----------- --------- ------------- ---------
#> **rowname aa a a a a a bbbb
#> one** aa bbbb
#> aa bbbb
#>
#> **rowname aaa aaaaa bb
#> two** aaa bbb
#> bbbb
#> ---------------------------------------------
#>
## when not enough reverting to default values
pandoc.table(y, split.cells = c(5, 2))
#> Warning: length of split.cells vector is smaller than data. Default value will be used for other cells
#> Warning: length of split.cells vector is smaller than data. Default value will be used for other cells
#>
#> ------------------------------------------------------
#> colname colname colname three
#> one two
#> ----------------- --------- --------- ----------------
#> **rowname one** aa aa a bbbb bbbb bbbb
#> aa a
#> a
#> a
#> a
#>
#> **rowname two** aaa aaaaa bb bbb bbbb
#> aaa
#> ------------------------------------------------------
#>
## split.cells with hyphenation
x <- data.frame(a = "Can be also supplied as a vector, for each cell separately",
b = "Can be also supplied as a vector, for each cell separately")
pandoc.table(x, split.cells = 10, use.hyphening = TRUE)
#>
#> -------------------------
#> a b
#> ------------ ------------
#> Can be al- Can be al-
#> so sup- so sup-
#> plied as a plied as a
#> vector, vector,
#> for each for each
#> cell sepa- cell sepa-
#> rately rately
#> -------------------------
#>