Init 🎉

.github/workflows/main.yml

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+name: Render and Deploy Quarto Site
+on:
+  push:
+    branches: main
+  # schedule:
+    # Runs daily at midnight (EST)
+    # - cron: '0 5 * * *'
+
+jobs:
+  build:
+    runs-on: macOS-latest
+    steps:
+      - uses: actions/checkout@v2
+      - uses: r-lib/actions/setup-r@v2
+      - uses: r-lib/actions/setup-pandoc@v2
+      - uses: quarto-dev/quarto-actions/setup@v2
+      - name: Query dependencies
+        run: |
+          options(download.file.method = "libcurl")
+          options(repos = "https://cran.rstudio.com")
+          install.packages('remotes')
+          saveRDS(remotes::dev_package_deps(dependencies = TRUE), ".github/depends.Rds", version = 2)
+        shell: Rscript {0}
+
+      - name: Cache R packages
+        uses: actions/cache@v1
+        with:
+          path: ${{ env.R_LIBS_USER }}
+          key: macOS-r-3.6-${{ hashFiles('.github/depends.Rds') }}
+          restore-keys: macOS-r-3.6-
+
+      - name: Install system dependencies
+        run: |
+          brew install libgit2
+
+      - name: Install dependencies
+        run: |
+          install.packages("remotes")
+          remotes::install_deps(dependencies = TRUE)
+        shell: Rscript {0}
+
+      - name: Publish to GitHub Pages (and render)
+        uses: quarto-dev/quarto-actions/publish@v2
+        with:
+          target: gh-pages
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

DESCRIPTION

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+Type: Website
+Package: emsep4a
+Title: EMSE 4571 - Intro to Programming for Analytics, Spring 2024
+Version: 1.0
+Maintainer: John Helveston <[email protected]>
+Author: John Helveston <[email protected]>
+Authors@R: c(
+    person("John", "Helveston", email = "[email protected]", role = c("aut", "cre")),
+    )
+Depends: R (>= 3.4.0)
+License: CC-BY-SA
+Encoding: UTF-8
+Imports:
+    countdown,
+    cowplot,
+    DAAG,
+    devtools,
+    dslabs,2
+    fastDummies,
+    fontawesome,
+    gapminder,
+    ggrepel,
+    ggthemes,
+    gsheet,
+    here,
+    hrbrthemes,
+    janitor,
+    kableExtra,
+    knitr,
+    logitr,
+    metathis,
+    nycflights13,
+    palmerpenguins,
+    remotes,
+    repurrrsive,
+    reticulate,
+    rmarkdown,
+    roxygen2,
+    tidyverse,
+    TurtleGraphics,
+    viridis,
+    viridisLite,
+    xaringanExtra,
+    wikifacts,
+    yaml

EMSE-P4A-2024-Spring.Rproj

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+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 4
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
+
+BuildType: Website

LICENSE.qmd

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+---
+title: "Licensing and copyright information"
+---
+
+The course material is licensed under the
+[Creative Commons ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-sa/4.0/). In addition to my own developed material, I have also modified material from
+the courses, workshops, and textbooks listed below:
+
+### Courses / workshops
+
+Name | Author(s) | Links
+--------- | --------- | ---
+STAT 545 | U. of British Columbia | [course](http://stat545.com/); [GitHub](https://github.com/STAT545-UBC)
+Patrick Meyer's Youtube lectures | Prof. Patrick Meyer | [playlists](https://www.youtube.com/channel/UCyTTRlOdjHg23q3l6_CD4gg/playlists)
+Andrew Heiss's data viz courses | Andrew Heiss | [MPA 635](https://datavizf17.classes.andrewheiss.com/), [more here](https://www.andrewheiss.com/teaching/)
+Intro. to Data Visualization, Fall 2018 | Peter Aldhous | [course site](https://paldhous.github.io/ucb/2018/dataviz/index.html)
+
+### Books
+
+Name | Author(s) | Links
+--------- | --------- | ---
+R for Data Science | Garrett Grolemund & Hadley Wickham | [online book](https://r4ds.had.co.nz/); [GitHub](https://github.com/hadley/r4ds); [purchase](https://www.amazon.com/Data-Science-Transform-Visualize-Model/dp/1491910399)
+Data Visualization: A practical introduction | Kieran Healy | [online book](http://socviz.co/); [GitHub](https://github.com/kjhealy/dataviz); [purchase](https://www.amazon.com/Data-Visualization-Introduction-Kieran-Healy/dp/0691181624)
+Fundamentals of Data Visualization | Claus O. Wilke | [online book](https://serialmentor.com/dataviz/); [purchase](https://www.amazon.com/Fundamentals-Data-Visualization-Informative-Compelling/dp/1492031089)

README.Rmd

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+---
+output:
+  github_document:
+    html_preview: false
+---
+
+<!-- README.md is generated from README.Rmd. Please edit that file -->
+
+## EMSE 4571: Intro. to Programming for Analytics (Spring 2024) <a href='https://github.com/emse-p4a-gwu/2024-Spring'><img src='images/logo.png' align="right" height="139"/></a>
+
+<!-- badges: start -->
+[![License: CC-BY-SA 4.0](https://img.shields.io/badge/License-CC%20BY--SA-lightgrey)](https://creativecommons.org/licenses/by-sa/4.0/)
+<!-- badges: end -->
+
+### Description
+
+```{r child = here::here("fragments", "description.qmd")}
+```
+
+For more details, please see the [course
+website](https://p4a.seas.gwu.edu/2024-Spring/).
+
+### Acknowledgments
+
+This course was inspired by many other courses / resources that cover
+similar material - see the course [about
+page](https://p4a.seas.gwu.edu/2024-Spring/about.html) for more details.

README.md

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+
+<!-- README.md is generated from README.Rmd. Please edit that file -->
+
+## EMSE 4571: Intro. to Programming for Analytics (Spring 2024) <a href='https://github.com/emse-p4a-gwu/2024-Spring'><img src='images/logo.png' align="right" height="139"/></a>
+
+<!-- badges: start -->
+
+[![License: CC-BY-SA
+4.0](https://img.shields.io/badge/License-CC%20BY--SA-lightgrey)](https://creativecommons.org/licenses/by-sa/4.0/)
+<!-- badges: end -->
+
+### Description
+
+This course provides a foundation in programming for analytics using the
+[R programming language](https://www.r-project.org/) with a comparison
+to [Python](https://www.python.org/). Topics covered include
+fundamentals of programming (operators, data types, objects, functions,
+conditionals, loops, strings, testing, and debugging) as well as
+techniques for working with data sets in R and Python (file
+input/output, data structures, data wrangling, data visualization,
+external packages, and reproducible reporting). Emphasis will be on
+producing clear, robust, and reasonably efficient code using top-down
+design, informal analysis, and effective testing and debugging. Students
+will primarily work on individual programming assignments to develop
+skills in computational problem solving, writing code, and working with
+data. Students will be assessed through quizzes, homework assignments,
+and exams. Teaching will involve interactive lectures with plenty of
+time spent live coding and working on practice problems in class. This
+course assumes no prior programming experience and is an ideal
+preparation for higher level courses in data analytics.
+
+For more details, please see the [course
+website](https://p4a.seas.gwu.edu/2024-Spring/).
+
+### Acknowledgments
+
+This course was inspired by many other courses / resources that cover
+similar material - see the course [about
+page](https://p4a.seas.gwu.edu/2024-Spring/about.html) for more details.

_common.R

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+set.seed(5678)
+
+options(
+    dplyr.width = Inf,
+    dplyr.print_min = 6,
+    dplyr.print_max = 6,
+    stringr.view_n = 10,
+    pillar.bold = TRUE,
+    width = 77 # 80 - 3 for #> comment
+)
+
+knitr::opts_chunk$set(
+    message = FALSE,
+    warning = FALSE,
+    comment    = "#>",
+    fig.retina = 3,
+    fig.width  = 6,
+    fig.height = 4,
+    fig.show = "hold",
+    fig.align  = "center",
+    fig.path   = "figs/"
+)
+
+get_schedule <- function() {
+
+    schedule_raw <- read_csv(here::here('schedule.csv'))
+
+    # Quiz vars
+    quiz <- schedule_raw %>%
+        mutate(
+            quiz = ifelse(
+                is.na(quiz),
+                "",
+                paste0('Quiz ', quiz, ":<br><em>", quiz_coverage, "</em>"))
+        ) %>%
+        select(week, quiz)
+
+    # Weekly assignment vars
+    assignments <- schedule_raw %>%
+        mutate(
+            due_assign = format(due_assign, format = "%b %d"),
+            assignments = ifelse(
+                is.na(due_assign),
+                "",
+                paste0(
+                    '<a href="hw/', n_assign, "-", stub_assign, '.html"><b>HW ',
+                    n_assign, "</b></a><br>Due: ", due_assign))
+        ) %>%
+        select(week, assignments)
+
+    # Class vars
+    class <- schedule_raw %>%
+        mutate(
+            description_class = ifelse(
+                is.na(description_class),
+                "",
+                description_class),
+            class = ifelse(
+                is.na(stub_class),
+                paste0("<b>", name_class, "</b><br>", description_class),
+                paste0(
+                    '<a href="class/', n_class, "-", stub_class, '.html"><b>',
+                    name_class, "</b></a><br> ",
+                    description_class)),
+        ) %>%
+        select(week, class)
+
+    # Reading vars
+    reading <- schedule_raw %>%
+        select(week, ends_with("_reading"), reading) %>%
+        rename(name = name_reading, stub = stub_reading) %>%
+        mutate(
+            name = str_split(name, '\n'),
+            stub = str_split(stub, '\n')
+        )
+
+    # Fix reading names
+    reading_root <- 'https://p4a.jhelvy.com/'
+    reading$readings <- ""
+    for (i in 1:nrow(reading)) {
+        name <- reading[i,]$name[[1]]
+        if (any(is.na(unlist(name)))) {
+            result <- ''
+        } else {
+            stub <- reading[i,]$stub[[1]]
+            result <- paste0(
+                '<a href=', reading_root, stub ,'.html target="_blank"><b>',
+                name, "</b></a>")
+            result <- paste(result, collapse = '<br>')
+
+        }
+        reading$readings[i] <- result
+    }
+    reading$name <- NULL
+    reading$stub <- NULL
+    reading <- reading %>% 
+        mutate(readings = ifelse(!is.na(reading), reading, readings))
+
+    # Final schedule data frame
+    schedule <- schedule_raw %>%
+        select(week, date, n_assign, due_assign) %>%
+        mutate(date_md = format(date, format = "%b %d")) %>%
+        left_join(quiz, by = "week") %>%
+        left_join(class, by = "week") %>%
+        left_join(assignments, by = "week") %>%
+        left_join(reading, by = "week") %>% 
+        ungroup()
+
+    return(schedule)
+}