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hrbrmstr / Waffle

🍁 Make waffle (square pie) charts in R

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waffle

Create Waffle Chart Visualizations

Description

Square pie charts (a.k.a. waffle charts) can be used to communicate parts of a whole for categorical quantities. To emulate the percentage view of a pie chart, a 10x10 grid should be used with each square representing 1% of the total. Modern uses of waffle charts do not necessarily adhere to this rule and can be created with a grid of any rectangular shape. Best practices suggest keeping the number of categories small, just as should be done when creating pie charts. Tools are provided to create waffle charts as well as stitch them together, and to use glyphs for making isotype pictograms.

It uses ggplot2 and returns a ggplot2 object.

What’s Inside the Tin

The following functions are implemented:

  • waffle: Make waffle (square pie) charts
  • draw_key_pictogram: Legend builder for pictograms
  • fa_grep: Search Font Awesome glyph names for a pattern
  • fa_list: List all Font Awesome glyphs
  • geom_pictogram: Pictogram Geom
  • geom_waffle: Waffle (Square pie chart) Geom
  • install_fa_fonts: Install Font Awesome 5 Fonts
  • iron: Veritical, left-aligned layout for waffle plots
  • scale_label_pictogram: Used with geom_pictogram() to map Font Awesome fonts to labels
  • theme_enhance_waffle: Waffle chart theme cruft remover that can be used with any other theme

Installation

install.packages("waffle", repos = "https://cinc.rud.is")
# or
devtools::install_git("https://git.rud.is/hrbrmstr/waffle.git")
# or
devtools::install_git("https://git.sr.ht/~hrbrmstr/waffle")
# or
devtools::install_gitlab("hrbrmstr/waffle")
# or
devtools::install_bitbucket("hrbrmstr/waffle")
# or
devtools::install_github("hrbrmstr/waffle")

Usage

library(waffle)
library(magrittr)
library(hrbrthemes)
library(ggplot2)
library(dplyr)
library(waffle)

# current verison
packageVersion("waffle")
## [1] '1.0.1'

Some new bits up first

data.frame(
  parts = factor(rep(month.abb[1:3], 3), levels=month.abb[1:3]),
  vals = c(10, 20, 30, 6, 14, 40, 30, 20, 10),
  col = rep(c("blue", "black", "red"), 3),
  fct = c(rep("Thing 1", 3),
          rep("Thing 2", 3),
          rep("Thing 3", 3))
) -> xdf

xdf %>%
  count(parts, wt = vals) %>%
  ggplot(aes(fill = parts, values = n)) +
  geom_waffle(n_rows = 20, size = 0.33, colour = "white", flip = TRUE) +
  scale_fill_manual(
    name = NULL,
    values = c("#a40000", "#c68958", "#ae6056"),
    labels = c("Fruit", "Sammich", "Pizza")
  ) +
  coord_equal() +
  theme_ipsum_rc(grid="") +
  theme_enhance_waffle()

xdf %>%
  count(parts, wt = vals) %>%
  ggplot(aes(label = parts, values = n)) +
  geom_pictogram(n_rows = 10, aes(colour = parts), flip = TRUE, make_proportional = TRUE) +
  scale_color_manual(
    name = NULL,
    values = c("#a40000", "#c68958", "#ae6056"),
    labels = c("Fruit", "Sammich", "Pizza")
  ) +
  scale_label_pictogram(
    name = NULL,
    values = c("apple-alt", "bread-slice", "pizza-slice"),
    labels = c("Fruit", "Sammich", "Pizza")
  ) +
  coord_equal() +
  theme_ipsum_rc(grid="") +
  theme_enhance_waffle() +
  theme(legend.key.height = unit(2.25, "line")) +
  theme(legend.text = element_text(size = 10, hjust = 0, vjust = 0.75))

xdf %>%
  count(parts, wt = vals) %>%
  ggplot(aes(label = parts, values = n)) +
  geom_pictogram(
    n_rows = 20, size = 6, aes(colour = parts), flip = TRUE,
    family = "FontAwesome5Brands-Regular"
  ) +
  scale_color_manual(
    name = NULL,
    values = c("#073f9c", "black", "#f34323"),
    labels = c("BitBucket", "GitHub", "Other")
  ) +
  scale_label_pictogram(
    name = NULL,
    values = c("bitbucket", "github", "git-alt"),
    labels = c("BitBucket", "GitHub", "Other")
  ) +
  coord_equal() +
  theme_ipsum_rc(grid="") +
  theme_enhance_waffle() +
  theme(legend.text = element_text(hjust = 0, vjust = 1))

Geoms!

library(hrbrthemes)
library(waffle)
library(tidyverse)

tibble(
  parts = factor(rep(month.abb[1:3], 3), levels=month.abb[1:3]),
  values = c(10, 20, 30, 6, 14, 40, 30, 20, 10),
  fct = c(rep("Thing 1", 3), rep("Thing 2", 3), rep("Thing 3", 3))
) -> xdf

ggplot(xdf, aes(fill=parts, values=values)) +
  geom_waffle(color = "white", size=1.125, n_rows = 6) +
  facet_wrap(~fct, ncol=1) +
  scale_x_discrete(expand=c(0,0)) +
  scale_y_discrete(expand=c(0,0)) +
  ggthemes::scale_fill_tableau(name=NULL) +
  coord_equal() +
  labs(
    title = "Faceted Waffle Geoms"
  ) +
  theme_ipsum_rc(grid="") +
  theme_enhance_waffle()

Waffle Bar Charts with scales!

library(dplyr)
library(waffle)

storms %>% 
  filter(year >= 2010) %>% 
  count(year, status) -> storms_df

ggplot(storms_df, aes(fill = status, values = n)) +
  geom_waffle(color = "white", size = .25, n_rows = 10, flip = TRUE) +
  facet_wrap(~year, nrow = 1, strip.position = "bottom") +
  scale_x_discrete() + 
  scale_y_continuous(labels = function(x) x * 10, # make this multiplyer the same as n_rows
                     expand = c(0,0)) +
  ggthemes::scale_fill_tableau(name=NULL) +
  coord_equal() +
  labs(
    title = "Faceted Waffle Bar Chart",
    subtitle = "{dplyr} storms data",
    x = "Year",
    y = "Count"
  ) +
  theme_minimal(base_family = "Roboto Condensed") +
  theme(panel.grid = element_blank(), axis.ticks.y = element_line()) +
  guides(fill = guide_legend(reverse = TRUE))

Basic example

parts <- c(80, 30, 20, 10)
waffle(parts, rows = 8)

Use a data frame

parts <- data.frame(
  names = LETTERS[1:4],
  vals = c(80, 30, 20, 10)
)

waffle(parts, rows = 8)

Slightly more complex example

parts <- c(`Un-breached\nUS Population` = (318 - 11 - 79), `Premera` = 11, `Anthem` = 79)
waffle(
  parts, rows = 8, size = 1, 
  colors = c("#969696", "#1879bf", "#009bda"), legend_pos = "bottom"
)

Health records breaches as fraction of US Population

One square == 1m ppl

waffle(
  parts / 10, rows = 3,
  colors = c("#969696", "#1879bf", "#009bda")
)

Health records breaches as fraction of US Population

(One square == 10m ppl)

library(extrafont)

waffle(
  parts / 10, rows = 3, colors = c("#969696", "#1879bf", "#009bda"),
  use_glyph = "medkit", size = 8
) + expand_limits(y = c(0, 4))

Replicating an old favourite

Via: https://www.nytimes.com/2008/07/20/business/20debt.html

savings <- c(
  `Mortgage\n($84,911)` = 84911, `Auto and\ntuition loans\n($14,414)` = 14414,
  `Home equity loans\n($10,062)` = 10062, `Credit Cards\n($8,565)` = 8565
)
waffle(
  savings / 392, rows = 7, size = 0.5, legend_pos = "bottom",
  colors = c("#c7d4b6", "#a3aabd", "#a0d0de", "#97b5cf")
)

Average Household Savings Each Year

(1 square == $392)

More replication

Similar to https://eagereyes.org/techniques/square-pie-charts

professional <- c(`Male` = 44, `Female (56%)` = 56)
waffle(
  professional, rows = 10, size = 0.5,
  colors = c("#af9139", "#544616")
)

Keeps factor by default levels now

With:

iron(
  waffle(c(thing1 = 0, thing2 = 100), rows = 5),
  waffle(c(thing1 = 25, thing2 = 75), rows = 5)
)

Without (you can disable this via keep parameter now):

iron(
  waffle(c(thing1 = 0, thing2 = 100), rows = 5, keep = FALSE),
  waffle(c(thing1 = 25, thing2 = 75), rows = 5, keep = FALSE)
)

Professional Workforce Makeup

Iron example (left-align & padding for multiple plots)

pain.adult.1997 <- c(`YOY (406)` = 406, `Adult (24)` = 24)

waffle(
  pain.adult.1997 / 2, rows = 7, size = 0.5,
  colors = c("#c7d4b6", "#a3aabd"),
  title = "Paine Run Brook Trout Abundance (1997)",
  xlab = "1 square = 2 fish", pad = 3
) -> A

pine.adult.1997 <- c(`YOY (221)` = 221, `Adult (143)` = 143)

waffle(
  pine.adult.1997 / 2, rows = 7, size = 0.5,
  colors = c("#c7d4b6", "#a3aabd"),
  title = "Piney River Brook Trout Abundance (1997)",
  xlab = "1 square = 2 fish", pad = 8
) -> B

stan.adult.1997 <- c(`YOY (270)` = 270, `Adult (197)` = 197)

waffle(
  stan.adult.1997 / 2, rows = 7, size = 0.5,
  colors = c("#c7d4b6", "#a3aabd"),
  title = "Staunton River Trout Abundance (1997)",
  xlab = "1 square = 2 fish"
) -> C

iron(A, B, C)

Package Code Metrics

cloc::cloc_pkg_md()
Lang # Files (%) LoC (%) Blank lines (%) # Lines (%)
R 16 0.89 628 0.62 209 0.61 430 0.7
Rmd 2 0.11 383 0.38 135 0.39 184 0.3

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