One of the main features of the tbl_df
class is the printing:
Tibbles only print as many rows and columns as fit on one screen, supplemented by a summary of the remaining rows and columns.
Tibble reveals the type of each column, which keeps the user informed about
whether a variable is, e.g., <chr>
or <fct>
(character versus factor).
Printing can be tweaked for a one-off call by calling print()
explicitly
and setting arguments like n
and width
. More persistent control is
available by setting the options described below.
Only the first 5 reduced dimensions are displayed, while all of them are queriable (e.g. ggplot). All dimensions are returned/displayed if as_tibble is used.
# S3 method for SingleCellExperiment
print(x, ..., n = NULL, width = NULL, n_extra = NULL)
Object to format or print.
Other arguments passed on to individual methods.
Number of rows to show. If NULL
, the default, will print all rows
if less than option tibble.print_max
. Otherwise, will print
tibble.print_min
rows.
Width of text output to generate. This defaults to NULL
, which
means use getOption("tibble.width")
or (if also NULL
)
getOption("width")
; the latter displays only the columns that fit on one
screen. You can also set options(tibble.width = Inf)
to override this
default and always print all columns.
Number of extra columns to print abbreviated information for,
if the width is too small for the entire tibble. If NULL
, the default,
will print information about at most tibble.max_extra_cols
extra columns.
Nothing
The following options are used by the tibble and pillar packages
to format and print tbl_df
objects.
Used by the formatting workhorse trunc_mat()
and therefore,
indirectly, by print.tbl()
.
tibble.print_max
: Row number threshold: Maximum number of rows printed.
Set to Inf
to always print all rows. Default: 20.
tibble.print_min
: Number of rows printed if row number threshold is
exceeded. Default: 10.
tibble.width
: Output width. Default: NULL
(use width
option).
tibble.max_extra_cols
: Number of extra columns printed in reduced form.
Default: 100.
library(dplyr)
pbmc_small %>% print()
#> # A SingleCellExperiment-tibble abstraction: 80 × 17
#> # Features=230 | Cells=80 | Assays=counts, logcounts
#> .cell orig.ident nCount_RNA nFeature_RNA RNA_snn_res.0.8 letter.idents groups
#> <chr> <fct> <dbl> <int> <fct> <fct> <chr>
#> 1 ATGC… SeuratPro… 70 47 0 A g2
#> 2 CATG… SeuratPro… 85 52 0 A g1
#> 3 GAAC… SeuratPro… 87 50 1 B g2
#> 4 TGAC… SeuratPro… 127 56 0 A g2
#> 5 AGTC… SeuratPro… 173 53 0 A g2
#> 6 TCTG… SeuratPro… 70 48 0 A g1
#> 7 TGGT… SeuratPro… 64 36 0 A g1
#> 8 GCAG… SeuratPro… 72 45 0 A g1
#> 9 GATA… SeuratPro… 52 36 0 A g1
#> 10 AATG… SeuratPro… 100 41 0 A g1
#> # ℹ 70 more rows
#> # ℹ 10 more variables: RNA_snn_res.1 <fct>, file <chr>, ident <fct>,
#> # PC_1 <dbl>, PC_2 <dbl>, PC_3 <dbl>, PC_4 <dbl>, PC_5 <dbl>, tSNE_1 <dbl>,
#> # tSNE_2 <dbl>