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[holtzy]

https://twitter.com/nrennie35/status/1761712006040592748

[JosephBARBIERDARNAL]

not reproducible ): it uses some personal functions that she wrote outside of the main script that I can't find.

I still put the .Rmd that I wrote here just in case:

---
title: "R Consortium ISC Grants: Voronoi Treemap Visualization"
descriptionMeta: "This post demonstrates how to create a Voronoi treemap in R to visualize R Consortium ISC grants using ggplot2, VoronoiPlus, and ggtext."
descriptionTop: "This post demonstrates how to create a Voronoi treemap in R to visualize the distribution of R Consortium ISC grants by project year using [ggplot2](ggplot2-package.html), [VoronoiPlus](package/VoronoiPlus.html), and [ggtext](package/ggtext.html). The chart **highlights the size of funding** for each project."
sectionText: "Voronoi Treemap"
sectionLink: "package/VoronoiPlus.html"
DataToVizText: "Data to Viz"
DataToVizLink: "data-to-viz.com/graph/treemap.html"
url: "web-voronoi-treemap-r-consortium"
output:
  html_document:
      self_contained: false    
      mathjax: default
      lib_dir: libs
      template: template_rgg.html
      css: style.css
      toc: TRUE
      toc_float: TRUE
      toc_depth: 2
      df_print: "paged"
---

```{r global options, include = FALSE}
knitr::opts_chunk$set(
   warning = FALSE,
   message = FALSE,
   fig.align = "center",
   fig.width = 12,
   fig.height = 7
)

About

---

This post visualizes the R Consortium ISC Grants by creating a Voronoi treemap. Each polygon in the treemap represents a different grant project, with the area of the polygon proportional to the funding amount. The treemap highlights the distribution of funds over different years and provides an insightful overview of the projects that received grants from the R Consortium Infrastructure Steering Committee (ISC).

It has been created by Nicola Rennie. Thanks to her for sharing this beautiful chart!

Libraries

---

To create this visualization, we will use several R packages: tidyverse for data manipulation, showtext for custom fonts, ggtext for enhanced text styling, and VoronoiPlus for generating the Voronoi treemap.

Install VoronoiPlus with devtools::install_github("AllanCameron/VoronoiPlus")

library(tidyverse)
library(showtext)
library(ggtext)
# library(nrBrand)
library(glue)
library(sf)
library(VoronoiPlus)

Dataset

---

The dataset is part of the TidyTuesday initiative and includes information about grants awarded by the R Consortium ISC. The dataset contains columns for the year the grant was awarded, whether the project was funded, and the project title.

tuesdata <- tidytuesdayR::tt_load("2024-02-20")
isc_grants <- tuesdata$isc_grants

The data is processed by selecting relevant columns, computing Voronoi polygons based on the grant data, and preparing labels for each year.

# Data wrangling
grant_data <- isc_grants |>
   select(year, funded, title)

vor_data <- voronoi_treemap(funded ~ year + title, data = grant_data)
set.seed(1234)
groups <- filter(vor_data, level == 1)
subgroups <- filter(vor_data, level == 2) |>
   group_by(group) |>
   mutate(alpha = runif(1, 0, 0.6)) |>
   ungroup()

year_labels <- groups |>
   select(group, x, y) |>
   st_as_sf(coords = c("x", "y")) |>
   group_by(group) |>
   summarise(geometry = st_combine(geometry)) |>
   st_cast("POLYGON") |>
   st_centroid() %>%
   mutate(
      x = st_coordinates(.)[, 1],
      y = st_coordinates(.)[, 2]
   ) |>
   st_drop_geometry()

Fonts and Colors

---

Custom fonts and colors are loaded to enhance the aesthetics of the plot. Google fonts Roboto and Roboto Slab are used for text, while a color palette from rcartocolor is applied to represent different years.

# Load fonts
font_add_google("Roboto", "roboto")
font_add_google("Roboto Slab", "robotoslab")
showtext_auto()

# Define colors and fonts
bg_col <- "#fafafa"
text_col <- "black"
highlight_col <- "#1c68bc"

cols_vec <- rcartocolor::carto_pal(length(unique(grant_data$year)) + 1, "Prism")[1:length(unique(grant_data$year))]
names(cols_vec) <- unique(grant_data$year)

body_font <- "roboto"
title_font <- "robotoslab"

Plotting

---

The final visualization is a Voronoi treemap that uses custom polygons to represent different grant projects, with labels indicating the year.

# Define text
social <- nrBrand::social_caption(
   bg_colour = bg_col,
   icon_colour = highlight_col,
   font_colour = text_col,
   font_family = body_font
)
title <- glue("<br><span style='font-size: 48px; font-weight: bold; font-family:{title_font};'>R Consortium ISC Grants</span><br><br>")
st <- glue("<span style='font-family:{body_font};'>The R Consortium Infrastructure Steering Committee (ISC) Grant Program has been awarding grants since 2016. They will accept proposals again between March 1 and April 1, 2024 (and then again in the fall). Each polygon represents a different project, with the size of the area representing the funding amount.</span><br><br>")
cap <- paste0(title, st, "**Data**: R Consortium ISC<br>**Graphic**:", social)

# Plot
ggplot() +
   geom_polygon(
      data = groups,
      mapping = aes(x = x, y = y, group = group, fill = group),
      colour = text_col,
      linewidth = 0.9
   ) +
   geom_polygon(
      data = subgroups,
      mapping = aes(x = x, y = y, group = group, alpha = alpha),
      fill = bg_col,
      colour = text_col,
      linewidth = 0.3
   ) +
   geom_polygon(
      data = groups,
      mapping = aes(x = x, y = y, group = group),
      colour = "transparent",
      fill = bg_col,
      alpha = 0.3,
      linewidth = 0.9
   ) +
   geom_text(
      data = year_labels,
      mapping = aes(x = x, y = y, label = group),
      colour = text_col,
      family = title_font,
      fontface = "bold",
      size = 12
   ) +
   scale_alpha_identity() +
   scale_fill_manual(values = cols_vec) +
   labs(
      caption = cap
   ) +
   coord_equal() +
   theme_void(base_size = 24, base_family = body_font) +
   theme(
      legend.position = "none",
      plot.margin = margin(-16, 0, 0, 0),
      plot.background = element_rect(fill = bg_col, colour = bg_col),
      panel.background = element_rect(fill = text_col, colour = text_col),
      plot.caption = element_textbox_simple(
         colour = text_col,
         hjust = 0,
         halign = 0,
         margin = margin(l = 10, t = 8),
         lineheight = 0.5,
         family = body_font
      )
   )

Going further

---

You might be interested in:

• Learning more about Voronoi diagrams
• How to create an interactive Voronoi treemap
• Explore other visualization techniques

htmltools::includeHTML("htmlChunkRelatedPartOfWhole.html")