On printing data frame: Set the following data frame
printing options to print all columns with the total number of rows set
by print_all_rows_max.
# set max number of rows to display
print_all_rows_max <- 6
# data.table syntax
half_max <- round(print_all_rows_max / 2, 0)
options(
datatable.print.nrows = print_all_rows_max,
datatable.print.topn = half_max
)
# dplyr/tibble syntax
options(
pillar.width = Inf,
pillar.print_max = print_all_rows_max,
pillar.print_min = print_all_rows_max
)For example
# data.table syntax
x <- copy(toy_student)
as.data.table(x)
#> mcid race sex institution transfer
#> <char> <char> <char> <char> <char>
#> 1: MCID3111142897 International Male Institution B First-Time Transfer
#> 2: MCID3111157634 White Female Institution J First-Time in College
#> 3: MCID3111158724 White Male Institution J First-Time in College
#> ---
#> 349: MCID3112868072 White Male Institution B First-Time in College
#> 350: MCID3112869843 White Female Institution B First-Time Transfer
#> 351: MCID3112885339 White Male Institution B First-Time in College
#> hours_transfer age_desc us_citizen home_zip high_school sat_math
#> <num> <char> <char> <char> <char> <num>
#> 1: NA Under 25 No <NA> <NA> NA
#> 2: NA Under 25 Yes 23842 471790 610
#> 3: NA Under 25 Yes 22026 471345 760
#> ---
#> 349: NA Under 25 Yes 98354 481345 670
#> 350: NA Under 25 Yes 80238 060400 NA
#> 351: NA Under 25 Yes 81615 060060 600
#> sat_verbal act_comp
#> <num> <num>
#> 1: NA NA
#> 2: 550 NA
#> 3: 560 NA
#> ---
#> 349: 460 25
#> 350: NA 28
#> 351: 640 29
# tibble syntax
library(tibble)
as_tibble(x)
#> # A tibble: 351 × 13
#> mcid race sex institution transfer
#> <chr> <chr> <chr> <chr> <chr>
#> 1 MCID3111142897 International Male Institution B First-Time Transfer
#> 2 MCID3111157634 White Female Institution J First-Time in College
#> 3 MCID3111158724 White Male Institution J First-Time in College
#> 4 MCID3111163443 White Male Institution J First-Time in College
#> 5 MCID3111163894 White Male Institution J First-Time in College
#> 6 MCID3111164659 White Male Institution J First-Time in College
#> hours_transfer age_desc us_citizen home_zip high_school sat_math sat_verbal
#> <dbl> <chr> <chr> <chr> <chr> <dbl> <dbl>
#> 1 NA Under 25 No NA NA NA NA
#> 2 NA Under 25 Yes 23842 471790 610 550
#> 3 NA Under 25 Yes 22026 471345 760 560
#> 4 NA Under 25 Yes 22075 471230 790 630
#> 5 NA Under 25 Yes 33157 101623 600 640
#> 6 NA Under 25 Yes 22207 470130 600 660
#> act_comp
#> <dbl>
#> 1 NA
#> 2 NA
#> 3 NA
#> 4 NA
#> 5 NA
#> 6 NA
#> # ℹ 345 more rows
# base R syntax
x <- as.data.frame(x)
head(x, n = print_all_rows_max)
#> mcid race sex institution transfer
#> 1 MCID3111142897 International Male Institution B First-Time Transfer
#> 2 MCID3111157634 White Female Institution J First-Time in College
#> 3 MCID3111158724 White Male Institution J First-Time in College
#> 4 MCID3111163443 White Male Institution J First-Time in College
#> 5 MCID3111163894 White Male Institution J First-Time in College
#> 6 MCID3111164659 White Male Institution J First-Time in College
#> hours_transfer age_desc us_citizen home_zip high_school sat_math sat_verbal
#> 1 NA Under 25 No <NA> <NA> NA NA
#> 2 NA Under 25 Yes 23842 471790 610 550
#> 3 NA Under 25 Yes 22026 471345 760 560
#> 4 NA Under 25 Yes 22075 471230 790 630
#> 5 NA Under 25 Yes 33157 101623 600 640
#> 6 NA Under 25 Yes 22207 470130 600 660
#> act_comp
#> 1 NA
#> 2 NA
#> 3 NA
#> 4 NA
#> 5 NA
#> 6 NA