Data visualization and storytelling

Materials for the "Data visualization and storytelling" PhD course, Fall 2024, University of Copenhagen

Teachers: Kaustubh Chakradeo, Jacob Curran-Sebastian, Neil Scheidwasser, Samir Bhatt

Setup

Setting up your DViz directory

It is recommended to download or clone the repo in a new directory.

For git users, use:

git clone https://github.com/ku-dviz/2024.git

Otherwise, download the repo as a .zip here and de-compress it.

Install R

• Download:
  • Windows: https://cran.r-project.org/bin/windows/base/R-4.4.0-win.exe
  • Mac (arm64; M1/M2 Macs): https://cran.r-project.org/bin/macosx/big-sur-arm64/base/R-4.4.0-arm64.pkg
  • Mac (x86): https://cran.r-project.org/bin/macosx/big-sur-x86_64/base/R-4.4.0-x86_64.pkg
  • Linux (Ubuntu): follow the instructions at https://cran.r-project.org/bin/linux/ubuntu/
• Follow the steps after running the executable file to install
• Check: open a terminal (in Windows, Command Prompt) and type R --> it should open an R console

Install RStudio

• Go to the RStudio website: https://posit.co/download/rstudio-desktop/
• Scroll down and download the appropriate version depending on your OS.
• Check: open RStudio, and check that the R version is the same as the one you installed

Install R Markdown

• We will use Rmarkdown to generate formated documents where text and code can be combined
• Installation:

install.packages('rmarkdown')

Data analysis and visualization packages

A basic setup with a comprehensive set of packages for scientific computing and data visualisation can be installed via the tidyverse package:

install.packages('tidyverse')

If you prefer to have a more minimal setup, you can install the following packages that are necessary for the exercises:

Basic data analysis:

install.packages(
  c(
    "dplyr", # Data manipulation
    "lubridate" # Date manipulation
    "gridExtra", # Grid graphics and subplots
    "ggplot2", # Graphics
    "readxl", # Excel I/O
    "ggspatial" # Spatial data framework for ggplot2
    "plotly", # Interactive plots
    "rnaturalearth", # Earth map data manipulation
    "rnaturalearhdata", # Earth vector map data
    "rnaturalearthhires", # High-resolution Earth vector map data
    "sf", # Simple Features manipulation (geographic data)
    "tmap", # (Interactive) thematic maps
    "corrplot", # Correlation matrix plots
    "uwot", # UMAP dimensionality reduction
    "daggity", # DAGs
    "ggdag", # Extension of daggity for ggplot2
    "igraph", # Network analysis
    "ggraph", # Networks in ggplot2
    "tidygraph", # Networks in the tidyverse
  )
)