КОМЕНТАРІ •

  • @rickymacharm4426
    @rickymacharm4426 2 місяці тому

    Another smooth one...moving on to the next one

  • @Uvinisihara
    @Uvinisihara 4 місяці тому

    Thank you so much for this video

  • @nickamato3021
    @nickamato3021 4 місяці тому

    Is this approach more lightweight for a server than building out a full blown RShiny app? Larger RShiny apps seem to be pretty demanding on the shiny-server running the app

    • @ggnot2
      @ggnot2 4 місяці тому +2

      For this *particular* approach (i.e., Quarto dashboard using GitHub Actions), it would need to be pretty lightweight since you're limited by GitHub's max repo size (50MB I believe) and by the maximum GitHub runner size (16GB RAM if using `ubuntu-latest` docs.github.com/en/actions/using-github-hosted-runners/about-github-hosted-runners/about-github-hosted-runners#standard-github-hosted-runners-for-public-repositories), whereas you can purchase more compute as needed for Shiny :) I haven't compared compute resource usage between the two, but from my understanding Quarto dashboards aren't really "running" anything after they've been initially rendered to the output format

  • @djangoworldwide7925
    @djangoworldwide7925 4 місяці тому +1

    Question: when you added unlist() to lapply, could you also just use sapplly, or that wouldn't work?
    I'm a bit new school and would probably go straight to map_chr, but I try to get familiar with base R map-like functions

    • @ggnot2
      @ggnot2 4 місяці тому

      I think sapply would work fine in this case!