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<!-- README.md is generated from README.Rmd. Please edit that file -->The flipbookr package
<!-- badges: start --> <!-- badges: end -->“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:
<img src="https://evamaerey.github.io/flipbookr/minimal_flipbook.gif" width="75%" style="display: block; margin: auto;" />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")