## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
message = FALSE,
warning = FALSE
)
## ----load-packages------------------------------------------------------------
library(afcharts)
library(ggplot2)
library(dplyr)
library(ggtext)
library(scales)
# Use gapminder data for cookbook charts
library(gapminder)
## ----line-charts-1------------------------------------------------------------
gapminder |>
filter(country == "United Kingdom") |>
ggplot(aes(x = year, y = lifeExp)) +
geom_line(linewidth = 1, colour = af_colour_values["dark-blue"]) +
theme_af() +
scale_y_continuous(
limits = c(0, 82),
breaks = seq(0, 80, 20),
expand = expansion(mult = c(0, 0.1))
) +
scale_x_continuous(breaks = seq(1952, 2007, 5)) +
labs(
x = "Year",
y = NULL,
title = "Living Longer",
subtitle = "Life Expectancy in the United Kingdom 1952-2007",
caption = "Source: Gapminder"
)
## ----line-charts-2, fig.height = 5--------------------------------------------
gapminder |>
filter(country %in% c("United Kingdom", "China")) |>
ggplot(aes(x = year, y = lifeExp, colour = country)) +
geom_line(linewidth = 1) +
theme_af(legend = "bottom") +
scale_colour_discrete_af() +
scale_y_continuous(
limits = c(0, 82),
breaks = seq(0, 80, 20),
expand = expansion(mult = c(0, 0.1))
) +
scale_x_continuous(breaks = seq(1952, 2007, 5)) +
labs(
x = "Year",
y = NULL,
title = "Living Longer",
subtitle = "Life Expectancy in the United Kingdom and China 1952-2007",
caption = "Source: Gapminder",
colour = NULL
)
## ----bar-data-----------------------------------------------------------------
pop_bar_data <- gapminder |>
filter(year == 2007 & continent == "Americas") |>
slice_max(order_by = pop, n = 5)
## ----bar-chart-1--------------------------------------------------------------
ggplot(pop_bar_data, aes(x = reorder(country, -pop), y = pop)) +
geom_col(fill = af_colour_values["dark-blue"]) +
theme_af() +
scale_y_continuous(
limits = c(0, 350E6),
labels = scales::label_number(scale = 1E-6),
expand = expansion(mult = c(0, 0.1)),
) +
labs(
x = NULL,
y = NULL,
title = stringr::str_wrap(
"The U.S.A. is the most populous country in the Americas",
40
),
subtitle = "Population of countries in the Americas (millions), 2007",
caption = "Source: Gapminder"
)
## ----bar-chart-2--------------------------------------------------------------
ggplot(pop_bar_data, aes(x = pop, y = reorder(country, pop))) +
geom_col(fill = af_colour_values["dark-blue"]) +
theme_af(grid = "x", axis = "y") +
scale_x_continuous(
limits = c(0, 350E6),
labels = scales::label_number(scale = 1E-6),
expand = expansion(mult = c(0, 0.1))
) +
labs(
x = NULL,
y = NULL,
title = stringr::str_wrap(
"The U.S.A. is the most populous country in the Americas",
40
),
subtitle = "Population of countries in the Americas (millions), 2007",
caption = "Source: Gapminder"
)
## ----grouped-bar-chart, fig.height = 5.5--------------------------------------
grouped_bar_data <-
gapminder |>
filter(
year %in% c(1967, 2007) &
country %in% c("United Kingdom", "Ireland", "France", "Belgium")
)
ggplot(
grouped_bar_data,
aes(x = country, y = lifeExp, fill = as.factor(year))
) +
geom_bar(stat = "identity", position = "dodge") +
scale_y_continuous(
limits = c(0, 100),
breaks = c(seq(0, 100, 20)),
labels = c(seq(0, 100, 20)),
expand = expansion(mult = c(0, 0.1))
) +
theme_af(legend = "bottom") +
scale_fill_discrete_af() +
labs(
x = "Country",
y = NULL,
fill = NULL,
title = "Living longer",
subtitle = "Difference in life expectancy, 1967-2007",
caption = "Source: Gapminder"
)
## ----stacked-bar-chart, fig.height = 5.5--------------------------------------
stacked_bar_data <-
gapminder |>
filter(year == 2007) |>
mutate(
lifeExpGrouped = cut(
lifeExp,
breaks = c(0, 75, Inf),
labels = c("Under 75", "75+")
)
) |>
group_by(continent, lifeExpGrouped) |>
summarise(n_countries = n(), .groups = "drop")
ggplot(
stacked_bar_data,
aes(x = continent, y = n_countries, fill = lifeExpGrouped)
) +
geom_bar(stat = "identity", position = "fill") +
theme_af(legend = "bottom") +
scale_y_continuous(
labels = scales::percent,
expand = expansion(mult = c(0, 0.1))
) +
coord_cartesian(clip = "off") +
scale_fill_discrete_af() +
labs(
x = NULL,
y = NULL,
fill = "Life Expectancy",
title = "How life expectancy varies across continents",
subtitle = "Percentage of countries by life expectancy band, 2007",
caption = "Source: Gapminder"
)
## ----histogram----------------------------------------------------------------
gapminder |>
filter(year == 2007) |>
ggplot(aes(x = lifeExp)) +
geom_histogram(
binwidth = 5,
colour = "white",
fill = af_colour_values["dark-blue"]
) +
theme_af() +
scale_y_continuous(
limits = c(0, 35),
breaks = c(seq(0, 35, 5)),
expand = expansion(mult = c(0, 0.1))
) +
labs(
x = NULL,
y = "Number of \ncountries",
title = "How life expectancy varies",
subtitle = "Distribution of life expectancy, 2007",
caption = "Source: Gapminder"
)
## ----scatterplot, fig.height = 5----------------------------------------------
gapminder |>
filter(year == 2007) |>
ggplot(aes(x = gdpPercap, y = lifeExp)) +
geom_point(colour = af_colour_values["dark-blue"]) +
theme_af(axis = "none", grid = "xy") +
scale_x_continuous(labels = scales::label_comma()) +
labs(
x = "GDP (US$, inflation-adjusted)",
y = "Life\nExpectancy",
title = stringr::str_wrap(
"The relationship between GDP and Life Expectancy is complex",
40
),
subtitle = "GDP and Life Expectancy for all countires, 2007",
caption = "Source: Gapminder"
)
## ----small-multiples, fig.height = 5.5----------------------------------------
gapminder |>
filter(continent != "Oceania") |>
group_by(continent, year) |>
summarise(pop = sum(as.numeric(pop)), .groups = "drop") |>
ggplot(aes(x = year, y = pop, fill = continent)) +
geom_area() +
theme_af(axis = "none", ticks = "none", legend = "none") +
scale_fill_discrete_af() +
facet_wrap(~ continent, ncol = 2) +
scale_y_continuous(
breaks = c(0, 2e9, 4e9),
labels = c(0, "2bn", "4bn")
) +
coord_cartesian(clip = "off") +
theme(axis.text.x = element_blank()) +
labs(
x = NULL,
y = NULL,
title = "Asia's rapid growth",
subtitle = "Population growth by continent, 1952-2007",
caption = "Source: Gapminder"
)
## ----pie-chart----------------------------------------------------------------
stacked_bar_data |>
filter(continent == "Europe") |>
ggplot(aes(x = "", y = n_countries, fill = lifeExpGrouped)) +
geom_col(colour = "white", position = "fill") +
coord_polar(theta = "y") +
theme_af(grid = "none", axis = "none", ticks = "none") +
theme(axis.text = element_blank()) +
scale_fill_discrete_af() +
labs(
x = NULL,
y = NULL,
fill = NULL,
title = "How life expectancy varies in Europe",
subtitle = "Percentage of countries by life expectancy band, 2007",
caption = "Source: Gapminder"
)
## ----focus-chart--------------------------------------------------------------
pop_bar_data |>
ggplot(aes(x = reorder(country, -pop), y = pop, fill = country == "Brazil")) +
geom_col() +
theme_af(legend = "none") +
scale_y_continuous(
limits = c(0, 350E6),
labels = scales::label_number(scale = 1E-6),
expand = expansion(mult = c(0, 0.1))
) +
scale_fill_discrete_af("focus", reverse = TRUE) +
labs(
x = NULL,
y = NULL,
title = stringr::str_wrap(
"Brazil has the second highest population in the Americas",
40
),
subtitle = "Population of countries in the Americas (millions), 2007",
caption = "Source: Gapminder"
)
## ----interactive-charts-------------------------------------------------------
p <-
pop_bar_data |>
# Format text for tooltips
mutate(
tooltip = paste0(
"Country: ", country, "\n",
"Population (millions): ", round(pop / 10 ^ 6, 1)
)
) |>
ggplot(aes(x = reorder(country, -pop), y = pop, text = tooltip)) +
geom_col(fill = af_colour_values["dark-blue"]) +
theme_af(ticks = "x") +
theme(text = element_text(family = "")) +
scale_y_continuous(
limits = c(0, 350E6),
labels = scales::label_number(scale = 1E-6),
expand = expansion(mult = c(0, 0.1))
) +
labs(
x = NULL,
y = "Population (millions)"
)
plotly::ggplotly(p, tooltip = "text") |>
plotly::config(
modeBarButtons = list(list("resetViews")),
displaylogo = FALSE
)
## ----annotations-data---------------------------------------------------------
ann_data <- gapminder |>
filter(country %in% c("United Kingdom", "China"))
## ----annotations-1------------------------------------------------------------
ann_data |>
ggplot(aes(x = year, y = lifeExp)) +
geom_line(
aes(colour = country),
linewidth = 1
) +
theme_af(legend = "none") +
scale_colour_discrete_af() +
scale_y_continuous(
limits = c(0, 82),
breaks = seq(0, 80, 20),
expand = expansion(mult = c(0, 0.1))
) +
scale_x_continuous(
limits = c(1952, 2017),
breaks = seq(1952, 2017, 5)
) +
annotate(
geom = "label",
x = 2008, y = 73,
label = "China",
label.size = NA,
hjust = 0,
vjust = 0.5
) +
annotate(
geom = "label",
x = 2008,
y = 79.4,
label = "United Kingdom",
label.size = NA,
hjust = 0,
vjust = 0.5
) +
labs(
x = "Year",
y = NULL,
title = "Living Longer",
subtitle = "Life Expectancy in the United Kingdom and China 1952-2007",
caption = "Source: Gapminder"
)
## ----annotations-2------------------------------------------------------------
ann_labs <- ann_data |>
group_by(country) |>
mutate(min_year = min(year)) |>
filter(year == max(year)) |>
ungroup()
ann_data |>
ggplot(aes(x = year, y = lifeExp)) +
geom_line(
aes(colour = country),
linewidth = 1
) +
theme_af(legend = "none") +
scale_colour_discrete_af() +
scale_y_continuous(
limits = c(0, 82),
breaks = seq(0, 80, 20),
expand = expansion(mult = c(0, 0.1))
) +
scale_x_continuous(
limits = c(1952, 2017),
breaks = seq(1952, 2017, 5)
) +
geom_label(
data = ann_labs,
aes(x = year, y = lifeExp, label = country),
hjust = 0,
vjust = 0.5,
nudge_x = 0.5,
label.size = NA
) +
labs(
x = "Year",
y = NULL,
title = "Living Longer",
subtitle = "Life Expectancy in the United Kingdom and China 1952-2007",
caption = "Source: Gapminder"
)
## ----annotations-3------------------------------------------------------------
ggplot(pop_bar_data, aes(x = reorder(country, -pop), y = pop)) +
geom_col(fill = af_colour_values["dark-blue"]) +
geom_text(
aes(label = round(pop / 1E6, 1)),
vjust = 1.2,
colour = "white"
) +
theme_af() +
scale_y_continuous(
limits = c(0, 350E6),
labels = scales::label_number(scale = 1E-6),
expand = expansion(mult = c(0, 0.1))
) +
labs(
x = NULL,
y = NULL,
title = stringr::str_wrap(
"The U.S.A. is the most populous country in the Americas",
40
),
subtitle = "Population of countries in the Americas (millions), 2007",
caption = "Source: Gapminder"
)
## ----sorting------------------------------------------------------------------
population_chart <- pop_bar_data |>
ggplot(aes(x = pop, y = reorder(country, pop))) +
geom_col(fill = af_colour_values["dark-blue"]) +
theme_af(axis = "y", grid = "x")
## ----chart-titles-------------------------------------------------------------
population_chart +
labs(
x = NULL,
y = NULL,
title = stringr::str_wrap(
paste("The U.S.A. has the highest population in the Americas"),
width = 40
),
subtitle = "Population of countries of the Americas (millions), 2007",
caption = "Source: Gapminder"
)
## ----expand-------------------------------------------------------------------
population_chart +
scale_x_continuous(expand = expansion(mult = c(0, 0.1)))
## ----axis-limits-breaks-labels-custom-----------------------------------------
population_chart +
scale_x_continuous(
breaks = seq(0, 400E6, 100E6),
labels = seq(0, 400, 100),
limits = c(0, 420E6),
expand = expansion(mult = c(0, 0.1))
) +
labs(
x = "Population (millions)"
)
## ----axis-limits-breaks-labels-fct--------------------------------------------
limits_pretty <- function(x) range(pretty(x))
population_chart +
scale_x_continuous(
breaks = pretty,
labels = label_number(scale = 1E-6),
limits = limits_pretty,
expand = expansion(mult = c(0, 0.2))
) +
labs(
x = "Population (millions)"
)
## ----using-scales, fig.height = 5.5-------------------------------------------
stacked_bar_data |>
ggplot(aes(x = continent, y = n_countries, fill = lifeExpGrouped)) +
geom_bar(stat = "identity", position = "fill") +
theme_af(legend = "bottom") +
scale_y_continuous(
expand = expansion(mult = c(0, 0.1)),
labels = scales::percent
) +
scale_fill_discrete_af() +
labs(
x = NULL,
y = NULL,
fill = "Life Expectancy",
title = "How life expectancy varies across continents",
subtitle = "Percentage of countries by life expectancy band, 2007",
caption = "Source: Gapminder"
)
## ----clip, fig.height = 5.5---------------------------------------------------
last_plot() + coord_cartesian(clip = "off")
## ----add-a-line---------------------------------------------------------------
gapminder |>
filter(country == "United Kingdom") |>
ggplot(aes(x = year, y = lifeExp)) +
geom_line(linewidth = 1, colour = af_colour_values[1]) +
geom_hline(
yintercept = 75,
colour = af_colour_values[2],
linewidth = 1,
linetype = "dashed"
) +
annotate(geom = "text", x = 2007, y = 70, label = "Age 70") +
theme_af() +
scale_y_continuous(
limits = c(0, 82),
breaks = seq(0, 80, 20),
expand = expansion(mult = c(0, 0.1))
) +
scale_x_continuous(breaks = seq(1952, 2007, 5)) +
labs(
x = "Year",
y = NULL,
title = "Living Longer",
subtitle = "Life Expectancy in the United Kingdom 1952-2007",
caption = "Source: Gapminder"
)
## ----text-wrap-1--------------------------------------------------------------
plot <-
ggplot(pop_bar_data, aes(x = reorder(country, -pop), y = pop)) +
geom_col(fill = af_colour_values["dark-blue"]) +
theme_af() +
scale_y_continuous(expand = expansion(mult = c(0, 0.1))) +
labs(
x = NULL,
subtitle = "Population of countries in the Americas (millions), 2007",
caption = "Source: Gapminder"
)
plot +
labs(
y = "Population of country",
title = paste("The U.S.A. is the most populous country in ",
"the Americas")
)
## ----text-wrap-2--------------------------------------------------------------
plot +
labs(
y = "Population\n of country",
title = stringr::str_wrap(
paste("The U.S.A. is the most populous country in ",
"the Americas"),
width = 40
)
)
## ----adjust-theme-------------------------------------------------------------
ggplot(pop_bar_data, aes(x = reorder(country, -pop), y = pop)) +
geom_col(fill = af_colour_values["dark-blue"]) +
theme_af(axis = "xy") +
theme(
axis.line = element_line(colour = "black"),
axis.ticks = element_line(colour = "black")
) +
scale_y_continuous(
expand = expansion(mult = c(0, 0.1)),
limits = c(0, 350E6),
labels = scales::label_number(scale = 1E-6)
) +
labs(
x = NULL,
y = NULL,
title = stringr::str_wrap(
"The U.S.A. is the most populous country in the Americas",
40
),
subtitle = "Population of countries in the Americas (millions), 2007",
caption = "Source: Gapminder"
)
## ----html-formatting----------------------------------------------------------
ann_data <- gapminder |>
filter(country %in% c("United Kingdom", "China"))
ann_labs <- ann_data |>
group_by(country) |>
mutate(min_year = min(year)) |>
filter(year == max(year)) |>
ungroup()
ann_data |>
ggplot(aes(x = year, y = lifeExp, colour = country)) +
geom_line(linewidth = 1) +
theme_af(legend = "none") +
scale_colour_discrete_af() +
scale_y_continuous(
limits = c(0, 82),
breaks = seq(0, 80, 20),
expand = expansion(mult = c(0, 0.1))
) +
scale_x_continuous(
limits = c(1952, 2017),
breaks = seq(1952, 2017, 5)
) +
geom_label(
data = ann_labs,
aes(x = year, y = lifeExp, label = country),
hjust = 0,
vjust = 0.5,
nudge_x = 0.5,
label.size = NA
) +
labs(
x = "Year",
y = NULL,
title = "Living Longer",
subtitle = "Life Expectancy in the
United Kingdom and
China 1952-2007",
caption = "Source: Gapminder"
) +
theme(plot.subtitle = element_markdown())
## ----af-palette, fig.height = 5-----------------------------------------------
gapminder |>
filter(country %in% c("United Kingdom", "China")) |>
ggplot(aes(x = year, y = lifeExp, colour = country)) +
geom_line(linewidth = 1) +
theme_af(legend = "bottom") +
scale_colour_discrete_af("main2") +
scale_y_continuous(
limits = c(0, 82),
breaks = seq(0, 80, 20),
expand = c(0, 0)
) +
scale_x_continuous(breaks = seq(1952, 2007, 5)) +
labs(
x = "Year",
y = NULL,
title = "Living Longer",
subtitle = "Life Expectancy in the United Kingdom and China 1952-2007",
caption = "Source: Gapminder",
colour = NULL
)
## ----different-colour-palette-1-----------------------------------------------
my_palette <- c("#0F820D", "#000000")
gapminder |>
filter(country == "United Kingdom") |>
ggplot(aes(x = year, y = lifeExp)) +
geom_line(linewidth = 1, colour = my_palette[1]) +
theme_af() +
scale_y_continuous(
limits = c(0, 82),
breaks = seq(0, 80, 20),
expand = c(0, 0)
) +
scale_x_continuous(breaks = seq(1952, 2007, 5)) +
labs(
x = "Year",
y = NULL,
title = "Living Longer",
subtitle = "Life Expectancy in the United Kingdom 1952-2007",
caption = "Source: Gapminder"
)
## ----different-colour-palette-2, fig.height = 5.5-----------------------------
gapminder |>
filter(country %in% c("United Kingdom", "China")) |>
ggplot(aes(x = year, y = lifeExp, colour = country)) +
geom_line(linewidth = 1) +
theme_af(legend = "bottom") +
scale_colour_manual(values = my_palette) +
scale_y_continuous(
limits = c(0, 82),
breaks = seq(0, 80, 20),
expand = c(0, 0)
) +
scale_x_continuous(breaks = seq(1952, 2007, 5)) +
labs(
x = "Year",
y = NULL,
title = "Living Longer",
subtitle = "Life Expectancy in the United Kingdom and China 1952-2007",
caption = "Source: Gapminder",
colour = NULL
)