R Markdown Advanced Tips to Become a Better Data Scientist & RStudio Connect | With Tom Mock

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  • Опубликовано: 18 окт 2024

Комментарии • 2

  • @jerrytang9514
    @jerrytang9514 10 месяцев назад

    This is it!!!!!!! The one tutorial that answered all my questions. Can't thank you enough.

  • @cynthiahuang7393
    @cynthiahuang7393 2 года назад +7

    04:15 Literate Programming
    09:00 - Rstudio Visual Editor Demo
    15:44 - R and python in same document via {reticulate}
    18:10 - Q&A: Options for collaborative editing (version control, shared drive etc.)
    19:30 - Q&A: Multi-pane support in Rstudio
    20:46 Data Product (reports, presentations, dashboards, websites etc.)
    24:15 - Distill article
    26:27 - Xaringan presentation (add three dashes --- for new slide)
    28:58 - Flexdashboard (with shiny)
    30:30 - Crosstalk (talk between different html widgets instead of {shiny} server)
    35:03 - Q&A: Jobs panel -- parallelise render jobs in background
    36:50 - Q&A: various data product packages, formats
    39:35 Control Document (modularise data science tasks, control code flow)
    39:58 - Knit with Parameters (YAML params: option)
    41:20 - Reference named chunks from .R files (knitr::read_chunk())
    43:00 - Child Documents (reuse content, conditional inclusion, {blastula} email)
    47:07 Templating (don't repeat yourself)
    47:38 - rmarkdown::render() with params, looping through different param combinations
    49:30 - loop templates within a single document
    50:40 - 04-templating/ live code demo
    54:37 - {whisker} vs {glue} -- {{logic-less}} vs {logic templating}
    55:30 - {whisker} for generating markdown files that you can continue editing
    57:49 RMarkdown + Rstudio Connect
    1:00:41 Follow-up Reading and resources
    1:04:49 Q&A - {shiny} apps, {webshot2} for screenshots of html, reading in multiple .R files, best practice for producing MSoffice files, {blastula}