The flipbookr package

“Flipbooks” present side-by-side, aligned, incremental code-output evolution via automated code parsing and reconstruction. Like physical flipbooks, they let the ‘reader’ watch a scene evolve at their own pace. Flipbooks seek to reduce the guesswork involved between code and its behavior by presenting substeps of a coding pipeline; the reader of a flipbook observes the partial code that is used to create “A.1”, “A.2”, “A.3” etc. all the way up to “B”.

Here’s the ‘minimal flipbook’ template that’s available with the package:

View flipbook in a new tab

The create a flipbook isn’t hard because parsing and reconstruction of code pipelines into substeps is automated!

flipbookr’s chunk_reveal() disassembles a single code chunk and creates the “build” of multiple partial-code chunks on different slides (the — is automatically generated for you too).

Check out the details on how to do this in this doublecrocheted version of the same flipbook (quotes the .Rmd source on some slides).

Installation

You can install the development version of flipbookr with devtools as follows:

devtools::install_github("EvaMaeRey/flipbookr")

You will most likely use this package with the rmarkdown presentation tool, Xaringan, which is available on CRAN:

install.packages("xaringan")

Template

The package includes several templates for building a flipbook that demonstrates various flipbooking modes.

The templates can be accessed from within RStudio. For example: New File -> RMarkdown -> From Template -> A Minimal Flipbook. The templates are:

• A Minimal Flipbook
• Most Flipbookr Features, preview output
• A Python Flipbook

How it works:

Here’s a flipbook going through some of the internal flipbookr functions.

library(tidyverse)
#> ── Attaching core tidyverse packages ─────────────────── tidyverse 2.0.0.9000 ──
#> ✔ dplyr     1.1.0     ✔ readr     2.1.4
#> ✔ forcats   1.0.0     ✔ stringr   1.5.0
#> ✔ ggplot2   3.4.4     ✔ tibble    3.2.1
#> ✔ lubridate 1.9.2     ✔ tidyr     1.3.0
#> ✔ purrr     1.0.1     
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag()    masks stats::lag()
#> ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
Titanic %>% 
  data.frame()
#>    Class    Sex   Age Survived Freq
#> 1    1st   Male Child       No    0
#> 2    2nd   Male Child       No    0
#> 3    3rd   Male Child       No   35
#> 4   Crew   Male Child       No    0
#> 5    1st Female Child       No    0
#> 6    2nd Female Child       No    0
#> 7    3rd Female Child       No   17
#> 8   Crew Female Child       No    0
#> 9    1st   Male Adult       No  118
#> 10   2nd   Male Adult       No  154
#> 11   3rd   Male Adult       No  387
#> 12  Crew   Male Adult       No  670
#> 13   1st Female Adult       No    4
#> 14   2nd Female Adult       No   13
#> 15   3rd Female Adult       No   89
#> 16  Crew Female Adult       No    3
#> 17   1st   Male Child      Yes    5
#> 18   2nd   Male Child      Yes   11
#> 19   3rd   Male Child      Yes   13
#> 20  Crew   Male Child      Yes    0
#> 21   1st Female Child      Yes    1
#> 22   2nd Female Child      Yes   13
#> 23   3rd Female Child      Yes   14
#> 24  Crew Female Child      Yes    0
#> 25   1st   Male Adult      Yes   57
#> 26   2nd   Male Adult      Yes   14
#> 27   3rd   Male Adult      Yes   75
#> 28  Crew   Male Adult      Yes  192
#> 29   1st Female Adult      Yes  140
#> 30   2nd Female Adult      Yes   80
#> 31   3rd Female Adult      Yes   76
#> 32  Crew Female Adult      Yes   20

Coming soon

chunk_reveal_live(chunk_name = "sample_chunk")