(╯°□°）╯︵ ┻━┻ {flippingtables} (╯°□°）╯︵ ┻━┻

All data.frame print methods are wrong, but some are useful

Inside you are two R users:

• One seeks meaning and truth in the numbers
• One seeks correctness and reproducibility in the code

The problem with all print() methods is that none can satisfy both users.

Methods like paint::paint(), pillar::glimpse(), and str() are pitched at the developer. They aim to succinctly display types, and convey a feel for the data with examples.

The default print.data.frame() aims to give the analyst all the numbers, and even does an okay job of it, provided you have a ultra-wide screen monitor, and less than a couple of hundred rows.

Others try to compromise between the two modalities, and they are generally the worst to use. They’ll consider the volume of data and space available, and concoct methods of truncation. Not rows, nor columns, nor column names, nor decimal places are held sacred. Using these involves a lot of retracing your steps fiddling with print arguments or setting options. It’s enough to make you want to flip tables.

You need multiple ways of printing data to suit whatever kind of user you happen to be today, and you need them arrayed easily at your fingertips to keep you in the zone. This package places the way you view your data in your session fully within your control.

Installation

remotes::install_github("MilesMcBain/flippingtables")

# and to try out the example configuration below:
install.packages("withr")
remotes::install_github("MilesMcBain/paint")

How to flip() tables

The setup is:

1. Create a configuration (probably in .Rprofile) with register_flips()

2. Enable the config with flip_on() (possibly in .Rprofile)

• may seem redundant but thank me when you need to flip_off() custom print methods because they balk at exotic text encodings or some such.

3. Use flip() to cycle between configured print methods for configured classes.

• Probably via a keyboard shortcut

Configuration

Here’s an example config:

library(flippingtables)
register_flips(
  printer_fns = list(
    paint::paint, # a pretty good option if I do say so myself.
    function(x) default_print(x, .args = list(print_arg(c("n", "max"), 100))), # a long format, uses .args see help(default_print)
    function(x) withr::with_options(list(width = 300), default_print(x)) # a wide format
  ),
  printed_classes = list(
    print_override(class = "tbl", pkg_namespace = "pillar"),
    print_override(class = "data.frame", pkg_namespace = "base"),
    print_override(class = "data.table", pkg_namespace = "data.table")
  )
)
#> [1] TRUE

flip_on() # now it's live!
#> Ready to flip tables.

First in printer_fns we declare the print methods we want be able to toggle between for use as the automatic print() in our R consolse sessions. Using anonymous functions is a great way to prototype custom print methods. The special function print_default() stands in for whatever the default print for the class being printed would normally be.

Then we nominate tbl, data.frame, and data.table as ‘flippable’ classes. We have to nominate the ‘top-level’ class that has the print method we want to override. I.e. even though tbl (a generic tibble used by {pillar}) and data.table are also data.frame we can’t just configure data.frame because objects of those classes have the "tbl" or "data.table" appear earlier in their vector of classes. This means their corresponding print() methods dispatched instead of print.data.frame (or the custom print method we routed that too).

Flipping

Calling flippingtables::flip() will advance the binding for the current print method to be used for all configured classes to the next one in the list. Print methods are cycled through in the order they are configured, and of course the cycle wraps around so cycling can happen endlessly.

If the last result (.Last.value) has a class that is configured for flipping, then the object is automatically re-printed with the new print method selected by flip().

Here’s how it might look:

# assuming config above
library(palmerpenguins)
penguins

# tibble [344, 8]
# species           fct Adelie Adelie Adelie Adelie Adelie Ad~
# island            fct Torgersen Torgersen Torgersen Torgers~
# bill_length_mm    dbl 39.1 39.5 40.3 NA 36.7 39.3
# bill_depth_mm     dbl 18.7 17.4 18 NA 19.3 20.6
# flipper_length_mm int 181 186 195 NA 193 190
# body_mass_g       int 3750 3800 3250 NA 3450 3650
# sex               fct male female female NA female male
# year              int 2007 2007 2007 2007 2007 2007

flip()

#  A tibble: 344 × 8
#     species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
#     <fct>   <fct>              <dbl>         <dbl>             <int>       <int>
#   1 Adelie  Torgersen           39.1          18.7               181        3750
#   2 Adelie  Torgersen           39.5          17.4               186        3800
#   3 Adelie  Torgersen           40.3          18                 195        3250
#   4 Adelie  Torgersen           NA            NA                  NA          NA
#   5 Adelie  Torgersen           36.7          19.3               193        3450

#   .. Output continues ..

#  95 Adelie  Dream               36.2          17.3               187        3300
#  96 Adelie  Dream               40.8          18.9               208        4300
#  97 Adelie  Dream               38.1          18.6               190        3700
#  98 Adelie  Dream               40.3          18.5               196        4350
#  99 Adelie  Dream               33.1          16.1               178        2900
# 100 Adelie  Dream               43.2          18.5               192        4100
# # ℹ 244 more rows
# # ℹ 2 more variables: sex <fct>, year <int>
# # ℹ Use `print(n = ...)` to see more rows

# it's sticky!
penguins

#  A tibble: 344 × 8
#     species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
#     <fct>   <fct>              <dbl>         <dbl>             <int>       <int>
#   1 Adelie  Torgersen           39.1          18.7               181        3750
#   2 Adelie  Torgersen           39.5          17.4               186        3800
#   3 Adelie  Torgersen           40.3          18                 195        3250
#   4 Adelie  Torgersen           NA            NA                  NA          NA
#   5 Adelie  Torgersen           36.7          19.3               193        3450

#   .. Output continues ..

#  95 Adelie  Dream               36.2          17.3               187        3300
#  96 Adelie  Dream               40.8          18.9               208        4300
#  97 Adelie  Dream               38.1          18.6               190        3700
#  98 Adelie  Dream               40.3          18.5               196        4350
#  99 Adelie  Dream               33.1          16.1               178        2900
# 100 Adelie  Dream               43.2          18.5               192        4100
# # ℹ 244 more rows
# # ℹ 2 more variables: sex <fct>, year <int>
# # ℹ Use `print(n = ...)` to see more rows

flip()

# # A tibble: 344 × 8
#    species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex     year
#    <fct>   <fct>              <dbl>         <dbl>             <int>       <int> <fct>  <int>
#  1 Adelie  Torgersen           39.1          18.7               181        3750 male    2007
#  2 Adelie  Torgersen           39.5          17.4               186        3800 female  2007
#  3 Adelie  Torgersen           40.3          18                 195        3250 female  2007
#  4 Adelie  Torgersen           NA            NA                  NA          NA NA      2007
#  5 Adelie  Torgersen           36.7          19.3               193        3450 female  2007
#  6 Adelie  Torgersen           39.3          20.6               190        3650 male    2007
#  7 Adelie  Torgersen           38.9          17.8               181        3625 female  2007
#  8 Adelie  Torgersen           39.2          19.6               195        4675 male    2007
#  9 Adelie  Torgersen           34.1          18.1               193        3475 NA      2007
# 10 Adelie  Torgersen           42            20.2               190        4250 NA      2007
# # ℹ 334 more rows
# # ℹ Use `print(n = ...)` to see more rows

Keyboard shortcut

In VSCode:

{
      "description": "flip() between print methods",
      "key": "<CHOOSE A KEYBINDING>",
      "command": "r.runCommand",
      "when": "editorTextFocus",
      "args": "flippingtables::flip()"
}

In RStudio:

• flip() is exposed as an RStudio addin, which can be bound to a keyboard shortcut. See instructions

In other editor:

• I think you should mostly be fine since it doesn’t depend on any editor state, but let me know if I can expose anything that makes it easier.

Cookbook

On of my personal favourites for looking at sumarised data analytically (provided it is sorted sensibly) is knitr::kable(). It has the added benefit that you can easily copy-paste the output to make nice tables in applications that speak markdown. It presents two problems for use directly:

• it doesn’t return the data it printed invisibly, unlike most methods intended to be used for this purpose. This will cause printing the .Last.value with flip() to stop as soon as this method is hit.
• it returns an object of a different class which has its own print method. R console seems not to like the idea of running through the print dispatch again, so we get nothing.

We work around this like so:

library(palmerpenguins)
library(flippingtables)
register_flips(
  printer_fns = list(
    paint = paint::paint, # a pretty good option if I do say so myself.
    kable = function(x) {
      print(knitr::kable(x))
      invisible(x)
    }
  ),
  printed_classes = list(
    print_override(class = "tbl", pkg_namespace = "pillar"),
    print_override(class = "data.frame", pkg_namespace = "base"),
    print_override(class = "data.table", pkg_namespace = "data.table")
  )
)
flip_on() # now it's live!
flip()
penguins
# Flipped print method to kable
# |species   |island    | bill_length_mm| bill_depth_mm| flipper_length_mm| body_mass_g|sex    | year|
# |:---------|:---------|--------------:|-------------:|-----------------:|-----------:|:------|----:|
# |Adelie    |Torgersen |           39.1|          18.7|               181|        3750|male   | 2007|
# |Adelie    |Torgersen |           39.5|          17.4|               186|        3800|female | 2007|
# |Adelie    |Torgersen |           40.3|          18.0|               195|        3250|female | 2007|
# .. Output continues ..