print prints its argument and returns it invisibly (via
invisible(x)). It is a generic function which means that
new printing methods can be easily added for new classes.
# S3 method for rxModelVars
print(x, ...)an object used to select a method.
further arguments passed to or from other methods.
This returns invisibly the model variables object
The default method, print.default has its own help page.
Use methods("print") to get all the methods for the
print generic.
print.factor allows some customization and is used for printing
ordered factors as well.
print.table for printing tables allows other
customization. As of R 3.0.0, it only prints a description in case of a table
with 0-extents (this can happen if a classifier has no valid data).
See noquote as an example of a class whose main
purpose is a specific print method.
Chambers, J. M. and Hastie, T. J. (1992) Statistical Models in S. Wadsworth & Brooks/Cole.
require(stats)
ts(1:20) #-- print is the "Default function" --> print.ts(.) is called
#> Time Series:
#> Start = 1
#> End = 20
#> Frequency = 1
#> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
for(i in 1:3) print(1:i)
#> [1] 1
#> [1] 1 2
#> [1] 1 2 3
## Printing of factors
attenu$station ## 117 levels -> 'max.levels' depending on width
#> [1] 117 1083 1095 283 135 475 113 1008 1028 2001 117 1117 1438 1083 1013
#> [16] 1014 1015 1016 1095 1011 1028 270 280 116 266 117 113 112 130 475
#> [31] 269 135 1093 1093 111 116 290 112 113 128 126 127 141 266 110
#> [46] 1027 111 125 135 475 262 269 1052 411 290 130 272 1096 1102 112
#> [61] 113 1028 2714 2708 2715 3501 655 272 1032 1377 1028 1250 1051 1293 1291
#> [76] 1292 283 885 <NA> 2734 <NA> 2728 1413 1445 1408 1411 1410 1409 1377 1492
#> [91] 1251 1422 1376 <NA> 286 <NA> 5028 942 <NA> 5054 958 952 5165 117 955
#> [106] 5055 <NA> <NA> 5060 412 5053 5058 5057 <NA> 5051 <NA> 5115 <NA> 931 5056
#> [121] 5059 5061 <NA> 5062 5052 <NA> 724 <NA> 5066 5050 2316 5055 942 5028 5165
#> [136] 952 958 955 117 412 5053 5054 5058 5057 5115 5056 5060 1030 1418 1383
#> [151] 1308 1298 1299 1219 <NA> <NA> 1030 1418 1383 <NA> 1299 1308 1219 1456 5045
#> [166] 5044 5160 5043 5047 c168 5068 c118 5042 5067 5049 c204 5070 c266 c203 5069
#> [181] 5073 5072
#> 117 Levels: 1008 1011 1013 1014 1015 1016 1027 1028 1030 1032 1051 1052 ... c266
## ordered factors: levels "l1 < l2 < .."
esoph$agegp[1:12]
#> [1] 25-34 25-34 25-34 25-34 25-34 25-34 25-34 25-34 25-34 25-34 25-34 25-34
#> Levels: 25-34 < 35-44 < 45-54 < 55-64 < 65-74 < 75+
esoph$alcgp[1:12]
#> [1] 0-39g/day 0-39g/day 0-39g/day 0-39g/day 40-79 40-79 40-79
#> [8] 40-79 80-119 80-119 80-119 120+
#> Levels: 0-39g/day < 40-79 < 80-119 < 120+
## Printing of sparse (contingency) tables
set.seed(521)
t1 <- round(abs(rt(200, df = 1.8)))
t2 <- round(abs(rt(200, df = 1.4)))
table(t1, t2) # simple
#> t2
#> t1 0 1 2 3 4 5 6 7 8 10 17 21 30
#> 0 21 22 14 4 1 0 1 1 1 0 1 0 0
#> 1 25 21 7 3 4 2 1 1 1 1 0 0 0
#> 2 8 16 9 2 0 0 0 0 0 0 0 1 1
#> 3 3 7 0 2 0 0 0 0 0 0 0 0 0
#> 4 1 5 2 0 0 0 1 0 0 0 0 0 0
#> 5 1 1 1 0 0 0 0 0 0 0 0 0 0
#> 6 1 3 0 0 0 0 0 0 0 0 0 0 0
#> 7 1 0 0 0 0 0 0 0 0 0 0 0 0
#> 9 0 0 0 1 0 0 0 0 0 0 0 0 0
#> 12 1 0 0 0 0 0 0 0 0 0 0 0 0
print(table(t1, t2), zero.print = ".") # nicer to read
#> t2
#> t1 0 1 2 3 4 5 6 7 8 10 17 21 30
#> 0 21 22 14 4 1 . 1 1 1 . 1 . .
#> 1 25 21 7 3 4 2 1 1 1 1 . . .
#> 2 8 16 9 2 . . . . . . . 1 1
#> 3 3 7 . 2 . . . . . . . . .
#> 4 1 5 2 . . . 1 . . . . . .
#> 5 1 1 1 . . . . . . . . . .
#> 6 1 3 . . . . . . . . . . .
#> 7 1 . . . . . . . . . . . .
#> 9 . . . 1 . . . . . . . . .
#> 12 1 . . . . . . . . . . . .
## same for non-integer "table":
T <- table(t2,t1)
T <- T * (1+round(rlnorm(length(T)))/4)
print(T, zero.print = ".") # quite nicer,
#> t1
#> t2 0 1 2 3 4 5 6 7 9 12
#> 0 26.25 25.00 10.00 3.75 1.50 1.25 1.25 1.00 . 2.00
#> 1 22.00 26.25 16.00 10.50 27.50 1.25 3.00 . . .
#> 2 21.00 7.00 13.50 . 3.00 1.25 . . . .
#> 3 5.00 3.75 2.50 2.50 . . . . 1.50 .
#> 4 1.25 5.00 . . . . . . . .
#> 5 . 2.00 . . . . . . . .
#> 6 1.25 1.50 . . 1.25 . . . . .
#> 7 1.25 1.25 . . . . . . . .
#> 8 1.50 1.00 . . . . . . . .
#> 10 . 1.00 . . . . . . . .
#> 17 1.00 . . . . . . . . .
#> 21 . . 2.75 . . . . . . .
#> 30 . . 5.00 . . . . . . .
print.table(T[,2:8] * 1e9, digits=3, zero.print = ".")
#> t1
#> t2 1 2 3 4 5 6 7
#> 0 2.50e+10 1.00e+10 3.75e+09 1.50e+09 1.25e+09 1.25e+09 1.00e+09
#> 1 2.62e+10 1.60e+10 1.05e+10 2.75e+10 1.25e+09 3.00e+09 .
#> 2 7.00e+09 1.35e+10 . 3.00e+09 1.25e+09 . .
#> 3 3.75e+09 2.50e+09 2.50e+09 . . . .
#> 4 5.00e+09 . . . . . .
#> 5 2.00e+09 . . . . . .
#> 6 1.50e+09 . . 1.25e+09 . . .
#> 7 1.25e+09 . . . . . .
#> 8 1.00e+09 . . . . . .
#> 10 1.00e+09 . . . . . .
#> 17 . . . . . . .
#> 21 . 2.75e+09 . . . . .
#> 30 . 5.00e+09 . . . . .
## still slightly inferior to Matrix::Matrix(T) for larger T
## Corner cases with empty extents:
table(1, NA) # < table of extent 1 x 0 >
#> < table of extent 1 x 0 >