heavywatal / slides

Home Page:https://heavywatal.github.io/slides/

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Slide decks

https://heavywatal.github.io/slides/

Framework

  1. knitr interprets code chunks in R Markdown source (content/*/.knitr/**.Rmd), and generates Markdown files (content/*/*.md) and figures (content/*/figure/*).
  2. Hugo converts Markdown files (content/*/*.md) to HTML files (public/*/*.html).
  3. reveal.js helps rendering HTML as presentation slides. KaTeX renders math equations ($ ... $ and \[ ... \]) embedded in HTML. They are included in a Hugo theme.
  4. The output and libraries are published via gh-pages branch of this repository.

But I recommend using Quarto Presentation via RStudio IDE. It is user-friendly and has decent defaults compared to older alternatives such as xaringan, rstudio/revealjs, and others supported in rmarkdown package.

R packages used in *.Rmd

install.packages("pak")
pak::repo_add(stan = "https://stan-dev.r-universe.dev")
pak::pkg_install("knitr")
pak::pkg_install("tidyverse")
pak::pkg_install("tidymodels")
pak::pkg_install("cowplot")
pak::pkg_install("ggrepel", "ggridges")
pak::pkg_install("palmerpenguins")
pak::pkg_install("nycflights13")
pak::pkg_install("gifski")
pak::pkg_install(c("cmdstanr", "bayesplot"))
pak::pkg_install(c("rstan", "rstanarm", "tidybayes"))
pak::pkg_install("heavywatal/rwtl")

Save as PDF

  1. Install nvm

  2. Install node: nvm install --lts --latest-npm

  3. Setup node: nvm use stable

  4. Change directory to this repo: cd ~/git/slides/

  5. Install decktape: npm install -g decktape

  6. Run decktape:

    decktape https://heavywatal.github.io/slides/tohoku2024r/1-introduction.html 1-introduction.pdf
    # or manually
    decktape -s 960x720 reveal https://heavywatal.github.io/slides/tohoku2024r/1-introduction.html 1-introduction.pdf
    decktape -s 800x600 automatic https://comicalcommet.github.io/r-training-2023/R_training_2023_1.html R_training_1.pdf

About

https://heavywatal.github.io/slides/

License:MIT License


Languages

Language:Jupyter Notebook 58.5%Language:Python 31.2%Language:R 7.0%Language:Makefile 2.5%Language:CSS 0.5%Language:Stan 0.2%