1 Software installation

Welcome to the Data Challenge Lab. Our hope is that this will be a fine learning experience for you. Please complete the steps below before our first meeting. They will prepare you to use the latest versions of Git, R, and RStudio.

1.1 Mac computers

Check that you have the program Applications > Utilities > XQuartz.
- If not, or if have an older version, download from the XQuartz download site and install.
Xcode command line tools
- Run Applications > Utilities > Terminal.
- At the prompt, enter the following command followed by a return:
  - xcode-select --install
- If the command line tools are not already installed, you will be prompted with a dialog box. Click on Install.

1.2 GitHub

We will be using GitHub in the DCL. If you don’t have a GitHub account:

Create a free GitHub account.

1.3 Git

Git is the software we will be using to access GitHub. Follow the instructions below to download and install the latest version. Note: to avoid problems, do not install any of the Git GUI clients.

Mac
- Download from Git download site.
- Click on the downloaded .dmg file.
- Right-click on the .pkg file and select Open.
- Follow installation instructions to install.
Windows
- Download from Git download site and install.
- Installation should include the Git Bash emulator.

1.4 R

We will be using some new R packages that require the latest version of R. Follow the instructions below to download and install this version.

If you already have R installed:
- Before installing a new version of R, save the names of your installed packages with the command
  - saveRDS(rownames(installed.packages()), file = "~/packages.rds")
Download the latest version of R from the R download site and install.
If you already had R installed:
- Restart R to launch the new installed version.
- Check to see if you now have the same packages with
  - if (!require("dplyr")) install.packages("dplyr")
  - dplyr::setequal(rownames(installed.packages()), readRDS("~/packages.rds"))
    - If TRUE, skip to last step
    - If FALSE, install the missing packages from CRAN with
      - install.packages(dplyr::setdiff(readRDS("~/packages.rds"), rownames(installed.packages())))
  - dplyr::setequal(rownames(installed.packages()), readRDS("~/packages.rds"))
    - If TRUE, skip to last step
    - If FALSE, install the missing packages not from CRAN. You can see the ones that are still missing with
      - dplyr::setdiff(readRDS("~/packages.rds"), rownames(installed.packages()))
- After you have installed all the packages you previously had, you can remove the file with the names of your installed packages with
  - unlink("~/packages.rds")

1.5 RStudio

If you don’t have RStudio, or don’t have the latest version:

Download and install the latest version of RStudio Desktop from its download site.

RStudio is constantly being updated with new features. It’s a good idea to update when RStudio indicates that a new version is available.

1.6 R packages

The power of R comes from its thousands of packages, such as the tidyverse. Follow the instructions below to install some of the packages we will be using.

Open up RStudio.
At the R prompt in the console in the lower-left corner, install the following packages with the command
- install.packages(c("tidyverse", "assertthat", "babynames", "broom", "compare", "DBI", "dbplyr", "devtools", "fivethirtyeight", "flexdashboard", "fs", "ggrepel", "googlesheets4", "hexbin", "httr", "janitor", "jsonlite", "knitr", "leaflet", "nycflights13", "RPostgreSQL", "rvest", "scales", "tidycensus", "usethis", "vroom", "yaml"))
Here’s a description of the packages installed:
- tidyverse is a collection of packages, some of which we will study in depth.
- assertthat is for making assertions within code.
- babynames is a dataset of baby names.
- broom is for working with models.
- compare will be used in exercises and challenges to compare solutions.
- DBI is for working with databases.
- dbplyr is for working with databases.
- devtools is a set of useful R development functions.
- fivethirtyeight is a dataset from the 538 blog.
- flexdashboard is for creating dashboards.
- fs is for file system operations.
- ggrepel is for automatically positioning labels in plots.
- googlesheets4 is for Google Sheets data.
- hexbin is for plots with hexagonal bins.
- httr is for web APIs.
- janitor is for examining and manipulating data.
- jsonlite is for JSON data.
- knitr is for document generation.
- leaflet is for interactive maps.
- nycflights13 is a dataset we will be using for the early exercises.
- RPostgreSQL is for working with the PostgreSQL database.
- rvest is for web scraping.
- scales is for scaling functions for visualization.
- tidycensus is for downloading U.S. Census data.
- usethis is for workflow tasks such as configuring your computer.
- vroom is for quickly reading and writing files.
- yaml is for YAML data.
Install the Data Challenge Lab (DCL) package.
- remotes::install_github("stanford-datalab/dcl")
Install a package with U.S. boundaries for maps
- remotes::install_github("dcl-docs/ussf")

1.7 Update R packages

Open RStudio.
Hit the Packages tab in the pane in the lower-right corner, and then the Update button.
Hit the Select All button, and then the Install Updates button.
If you are prompted to restart your R session, select Yes.
After the installations complete, your R packages will now be up to date.
It’s a good idea to periodically repeat this procedure to update your packages.

1.8 Configure RStudio

Carefully perform the following configuration steps:
- Tools (on RStudio menu bar) > Global Options…
  - General > Basic
    - Workspace
      - Restore .RData into workspace at startup: unchecked
      - Save workspace to .RData on exit: Never
    - History
      - Always save history (even when not saving .RData): unchecked
    - Other
      - Automatically notify me of updates to RStudio: checked
  - General > Advanced
    - OS Integration
      - Rendering engine:
        
        Mac: Auto-detect (recommended)
        
        Windows: Desktop OpenGL
  - Code
    - Editing
      - Insert spaces for tab: checked
      - Tab width: 2
      - Use native pipe operator, |> (requires R 4.1+): checked
    - Display
      - General
        
        Show margin: checked
        
        Margin column: 80
    - Saving
      - General
        
        Ensure that source files end with newline: checked
    - Diagnostics
      - R Diagnostics
        
        Show diagnostics for R: checked
        
        Enable diagnostics with R function calls: checked
        
        Provide R style diagnostics (e.g. whitespace): checked
  - R Markdown
    - Basic
      - R Markdown
        
        Show output inline for all R Markdown documents: checked
    - Advanced
      - Display
        
        Show inline toolbar for R code chunks: checked