• PhD Statistics and Operational Research

• Data scientist at Jumping Rivers

  • Consultancy: shiny, statistics, slides, …
  • Internal projects: blogdown websites, reports, plot styling, admin, …
  • Training: all things R (and some Tableau coming soon…)

• A lot of data visualisation…

• Compulsory R coursework for a statistics course during undergraduate degree
• Learnt Python instead…
• Final year of undergrad gave R another go
• Started learning {tidyverse} during PhD

• Data visualisation challenge where participants make one chart each day inspired by a daily prompt and category.
• Organised by Cédric Scherer and Dominic Royé, with support from Wendy Shijia and Marco Sciaini.
• Post charts on Twitter with the #30DayChartChallenge (and #DayX)
• See also: 30daychartchallenge.org

• One “new tool” for each of the five categories
• Learn some new things
• Make charts that I wanted to make
• Have fun!

• R packages
  • facet_zoom() from {ggforce}
  • Quarto
  • {tidytext}
• Non-R tools can be very helpful…
• Repeating styles should be bundled into an R package

• Time
  • Didn’t make charts each day, took breaks, reuse data
• Fitting my ideas and things I wanted to try to fit prompts
  • More planning

• {grid}
• {DiagrammeR}
• {igraph}
• {ggnetwork} / {ggnet2} / {ggraph}
• {tikz} (LaTeX)
• others…

Let’s try to make a flowchart with {ggplot2}…

library(tidyverse)
library(igraph)
library(showtext)
library(rcartocolor)

goldilocks <- tibble(from = c("Goldilocks",
                              "Porridge", "Porridge", "Porridge",
                              "Just right",
                              "Chairs", "Chairs", "Chairs",
                              "Just right2",
                              "Beds", "Beds", "Beds",
                              "Just right3"),
                     to = c("Porridge",
                            "Too cold", "Too hot", "Just right",
                            "Chairs",
                            "Still too big", "Too big", "Just right2",
                            "Beds",
                            "Too soft", "Too hard", "Just right3",
                            "Bears!"))

## # A tibble: 6 × 2
##   from       to           
##   <chr>      <chr>        
## 1 Goldilocks Porridge     
## 2 Porridge   Too cold     
## 3 Porridge   Too hot      
## 4 Porridge   Just right   
## 5 Just right Chairs       
## 6 Chairs     Still too big

g = graph_from_data_frame(goldilocks, directed = TRUE)
coords = layout_as_tree(g)
colnames(coords) = c("x", "y")

##       x y
## [1,]  0 7
## [2,]  0 6
## [3,] -1 5
## [4,] -1 4
## [5,] -2 3
## [6,] -2 2

output_df = as_tibble(coords) %>%
  mutate(step = vertex_attr(g, "name"),
         x = x*-1,
         type = factor(c(1, 2, 3, 2, 3, 2, 3, 3, 3, 3, 3, 3, 3, 1)),
         label = gsub("\\d+$", "", step))

## # A tibble: 6 × 5
##       x     y step        type  label     
##   <dbl> <dbl> <chr>       <fct> <chr>     
## 1     0     7 Goldilocks  1     Goldilocks
## 2     0     6 Porridge    2     Porridge  
## 3     1     5 Just right  3     Just right
## 4     1     4 Chairs      2     Chairs    
## 5     2     3 Just right2 3     Just right
## 6     2     2 Beds        2     Beds

plot_nodes = output_df %>%
  mutate(xmin = x - 0.35,
         xmax = x + 0.35,
         ymin = y - 0.25,
         ymax = y + 0.25)

## # A tibble: 6 × 9
##       x     y step        type  label       xmin  xmax  ymin  ymax
##   <dbl> <dbl> <chr>       <fct> <chr>      <dbl> <dbl> <dbl> <dbl>
## 1     0     7 Goldilocks  1     Goldilocks -0.35  0.35  6.75  7.25
## 2     0     6 Porridge    2     Porridge   -0.35  0.35  5.75  6.25
## 3     1     5 Just right  3     Just right  0.65  1.35  4.75  5.25
## 4     1     4 Chairs      2     Chairs      0.65  1.35  3.75  4.25
## 5     2     3 Just right2 3     Just right  1.65  2.35  2.75  3.25
## 6     2     2 Beds        2     Beds        1.65  2.35  1.75  2.25

plot_edges = goldilocks %>%
  mutate(id = row_number()) %>%
  pivot_longer(cols = c("from", "to"),
               names_to = "s_e",
               values_to = "step") %>%
  left_join(plot_nodes, by = "step") %>%
  select(-c(label, type, y, xmin, xmax)) %>%
  mutate(y = ifelse(s_e == "from", ymin, ymax)) %>%
  select(-c(ymin, ymax))

## # A tibble: 3 × 5
##      id s_e   step           x     y
##   <int> <chr> <chr>      <dbl> <dbl>
## 1     1 from  Goldilocks     0  6.75
## 2     1 to    Porridge       0  6.25
## 3     2 from  Porridge       0  5.75

• Google fonts and the {showtext} package
• Browse fonts: fonts.google.com

library(showtext)
font_add_google(name = "Henny Penny", family = "henny")
showtext_auto()

p = ggplot() +
  # draw rectangles
  geom_rect(data = plot_nodes,
            mapping = aes(xmin = xmin, ymin = ymin, xmax = xmax, ymax = ymax, 
                          fill = type, colour = type),
            alpha = 0.5,
            linejoin = "round") +
  # add text labels
  geom_text(data = plot_nodes,
            mapping = aes(x = x, y = y, label = label),
            family = "henny",
            color = "#585c45") +
  # add arrows
  geom_path(data = plot_edges,
            mapping = aes(x = x, y = y, group = id),
            colour = "#585c45",
            arrow = arrow(length = unit(0.3, "cm"), type = "closed"))

p

• {rcartocolor}: jakubnowosad.com/rcartocolor

p = p + 
  scale_fill_carto_d(palette = "Antique") +
  scale_colour_carto_d(palette = "Antique")

p

p = p + 
  labs(title = "The Goldilocks Decision Tree",
       caption = "N. Rennie\n\nData: Robert Southey. Goldilocks and the Three Bears. 
       1837.\n\nImage: New York Public Library\n\n#30DayChartChallenge") 

p

• Choose image
• Extract hex colour: imagecolorpicker.com

p = p + 
  theme_void() +
  theme(plot.margin = unit(c(1, 1, 0.5, 1), "cm"),
        legend.position = "none",
        plot.background = element_rect(colour = "#f2e4c1", fill = "#f2e4c1"),
        panel.background = element_rect(colour = "#f2e4c1", fill = "#f2e4c1"),
        plot.title = element_text(family = "henny", hjust = 0, face = "bold",
                                  size = 40, color = "#585c45",
                                  margin = margin(t = 10, r = 0, b = 10, l = 0)),
        plot.caption = element_text(family = "henny", hjust = 0,
                                    size = 10, color = "#585c45",
                                    margin = margin(t = 10)))

p

• {magick} and {cowplot}
• Inkscape: inkscape.org