Package
ggplot2 (Wickham 2016)
Description
Draw a horizontal line (\(Y=c\)) for a given value of \(c\), which is known as yintercept.
Understandable aesthetics
Unlike most other geoms, geom_hline does not depend on the x and y variables that we map for the main plot. geom_hline has its own independent characteristics: yintercept. The yintercept can be passed either as a arguments or aesthetic.
See also
geom_point, geom_vline, geom_hline
Example
a1 <- ggplot(worldbankdata, aes(y = Cooking, x= Electricity)) + geom_hline(yintercept = 50) +
labs(title="a1: `geom_hline` only") +
theme(aspect.ratio = 1)
a2 <- ggplot(worldbankdata, aes(y = Cooking, x=Electricity)) +
geom_point() +
geom_hline(yintercept = 50) +
labs(title="a2: `geom_point +\n geom_hline` both") +
theme(aspect.ratio = 1)
a1 | a2
Package
ggplot2 (Wickham 2016)
Description
Visualise data using histogram.
Understandable aesthetics
Unlike most other geoms, geom_hline does not depend on the x and y variables that we map for the main plot. geom_hline has its own independent characteristics: yintercept. The yintercept can be passed either as a arguments or aesthetic.
See also
geom_density, geom_density_line, geom_freqpoly
Example
worldbankdata |>
filter(Income == "LM") |>
ggplot(aes(x = Electricity)) +
geom_histogram(col="white")
Package
ggplot2 (Wickham 2016)
Description
Visualize numeric data using histogram and filled with patterns.
Understandable aesthetics
required aesthetics
x or y
optional aesthetics
alpha, colour, group, linetype, linewidth
See also
geom_histogram, geom_density, geom_density_line
worldbankdata |>
filter(Income == "LM") |>
ggplot(aes(x = Electricity)) +
geom_histogram_pattern( pattern_color = "white",
pattern_fill = "black")
Package
gghdr (gghdr?)
Description
Calculates and plots the box plot of highest density regions.
Understandable aesthetics
required aesthetics
x or y
optional aesthetics
alpha, colour
See also
geom_boxplot, geom_histogram, geom_density, geom_density_line
Example
library(gghdr)
worldbankdata |>
dplyr::filter(Year == 2021) |>
dplyr::select(Cooking) |>
ggplot(aes(y = Cooking, x=factor(0))) +
geom_hdr_boxplot(fill = "#081d58") Package
gghdr (gghdr?)
Description
Calculates and plots the box plot of highest density regions.
Understandable aesthetics
required aesthetics
x or y
optional aesthetics
alpha, colour, fill, group, linetype, linewidth
See also
geom_boxplot, geom_histogram, geom_density, geom_density_line
Example
library(hexbin)
library(viridis)
worldbankdata |>
filter(Income == "LM") |>
ggplot(aes(y = Cooking, x=Electricity)) +
geom_hex() +
scale_fill_viridis()
Package
ggDoubleHeat (Yu and Buskirk 2023)
Description
Visualize two quantitative variables of information inside a heatmap cell using a grid.
Understandable aesthetics
required aesthetics
x, y, outside, inside
Optional aesthetics
outside_colors, outside_name, inside_colors, inside_name
See also
geom_heat_circle, geom_heat_tri
Example
library(ggDoubleHeat)
worldbankdata[254:263, ] |>
ggplot(aes(y = Year, x=Income)) +
geom_heat_grid(outside = Electricity,
inside = Cooking) 
Package
ggDoubleHeat (Yu and Buskirk 2023)
Description
Visualize two quantitative variables of information inside a heatmap cell using triangles.
Understandable aesthetics
required aesthetics
x, y, lower, upper
Optional aesthetics
lower_colors, lower_name, upper_colors, upper_name
See also
Example
library(ggDoubleHeat)
worldbankdata[254:263, ] |>
ggplot(aes(y = Year, x=Income)) +
geom_heat_tri(lower = Electricity,
upper = Cooking) 
Package
ggDoubleHeat (Yu and Buskirk 2023)
Description
Visualize two quantitative variables of information inside a heatmap cell using triangles.
Understandable aesthetics
required aesthetics
x, y, outside, inside
Optional aesthetics
outside_colors, outside_name, inside_colors, inside_name
See also
Example
library(ggDoubleHeat)
worldbankdata[254:263, ] |>
ggplot(aes(y = Year, x=Income)) +
geom_heat_circle(outside = Electricity,
inside = Cooking) 
Package
ggplot2 (Wickham 2016)
Description
Draw a horizontal line given intercept.
Understandable aesthetics
Unlike most other geoms, geom_hline does not depend on the x and y variables that we map for the main plot.
See also
geom_point, geom_vline, geom_abline
Example
a1 <- ggplot(worldbankdata, aes(y = Cooking, x=Electricity)) +
geom_hline(yintercept = 50) +
labs(title="a1: geom_abline only") +
theme(aspect.ratio = 1)
a2 <- ggplot(worldbankdata, aes(y = Cooking, x=Electricity)) +
geom_hline(yintercept = 50) +
geom_point() +
labs(title = "a2: geom_hline \n and geom_point") +
theme(aspect.ratio = 1)
a1 | a2