ggplot2 - line thickness as a legend - r

Question

I would really appreciate it if anyone can help me use the thickness of the lines as a legend.
Thin line = low correlation
Think line = High correlation
I tried using the size of the dots to show the thickness but it confuses the audience even further. I am open to other creative methods to communicate this message to the audience.
My code is listed below.
Thanks in advance!
library(ggplot2)
# custom empty theme to clear the plot area
empty_theme <- theme(
plot.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.line = element_blank(),
axis.ticks = element_blank(),
axis.text.y = element_text(angle = 90)
)
plot <- ggplot(NULL, aes()) +
# fix the scale so it's always a square
coord_fixed() +
# set the scale to one greater than 0-10 in each direction
# this gives us some breating room and space to add some arrows
scale_x_continuous(expand = c(0, 0), limits = c(-1, 11),
breaks = c(2,8), labels=c("2" = "", "8" = "")) +
scale_y_continuous(expand = c(0, 0), limits = c(-1,11),
breaks = c(2,8), labels=c("2" = "", "8" = "")) +
# apply the empty theme
empty_theme +
# labels
labs(title = "Magic Quadrant",
x = "Completeness of Vision",
y = "Ability to Execute") +
# create the quadrants
geom_segment(aes(x = 10, y = 0, xend = 10, yend = 10), color = "#EDEDED") +
geom_segment(aes(x = 0, y = 0, xend = 0, yend = 10), color = "#EDEDED") +
geom_segment(aes(x = 0, y = 0, xend = 10, yend = 0), color = "#EDEDED") +
geom_segment(aes(x = 0, y = 5, xend = 10, yend = 5), color = "#EDEDED") +
geom_segment(aes(x = 5, y = 0, xend = 5, yend = 10), color = "#EDEDED") +
geom_segment(aes(x = 0, y = 10, xend = 10, yend = 10), color = "#EDEDED") +
#Rectangle
geom_rect(mapping = aes(xmin = 0, xmax = 5, ymin = 0, ymax = 5), fill = "#deecff") +
geom_rect(mapping = aes(xmin = 5, xmax = 10, ymin = 5, ymax = 10), fill = "#deecff") +
# quadrant labels
annotate("text", x = 2.5, y = 2.5, alpha = 0.35, label = "Niche Players", color = "#979b9c") +
annotate("text", x = 2.5, y = 7.5, alpha = 0.35, label = "Challengers", color = "#979b9c") +
annotate("text", x = 7.5, y = 2.5, alpha = 0.35, label = "Visionaries", color = "#979b9c") +
annotate("text", x = 7.5, y = 7.5, alpha = 0.35, label = "Leaders", color = "#979b9c") +
# arrows are cut in half which conveniently matches the gartner one
annotate("segment", x = 0, xend = 10, y = -1, yend = -1,colour = "blue",
size=2, alpha=1, arrow=arrow(type = "closed", angle = 15)) +
annotate("segment", x = -1, xend = -1, y = 0, yend = 10, colour = "blue",
size=2, alpha=1, arrow=arrow(type = "closed", angle = 15))
tools_quad_data <- data.frame(
title = c("A", "B", "C", "D", "E"),
value = c(6,6,6.3,6,8),
effort = c(3,8,9,4,7.9),
txt_position_value = c(6,6,6,6.2,8),
txt_position_effort = c(3.3,8.3,9.3,4.3,8.2)
)
plot <- plot +
geom_point(data = tools_quad_data, aes(x = value, y = effort, color = "ML Tool"), size = 4) +
geom_text(data = tools_quad_data, aes(label = title, x = txt_position_value, y = txt_position_effort), color = "#011d80")
db_quad_data <- data.frame(
title = c("U","V", "W","X","Y","Z"),
value = c(6.5,9,7.3,8,2,1),
effort = c(2.2, 9, 1, 3.4,1.5,0.1),
txt_position_value = c(6.7, 9.2, 7,8,2.2,1.3),
txt_position_effort = c(2,9.3, 0.7,3.1,1.3, 0.35)
)
plot <- plot +
geom_point(data = db_quad_data, aes(x = value, y = effort, color = "Database"), size = 4) +
geom_text(data = db_quad_data, aes(label = title, x = txt_position_value, y = txt_position_effort ), color = "#e09900") +
scale_colour_manual(name="Legend", values=c(Database="#e09900", `ML Tool`="#011d80"))
plot +
geom_curve(aes(x = 6.3, y = 9, xend = 2, yend = 1.5),
color = "black", curvature = 0.2, size = 0.5, alpha = 0.1) +
geom_curve(aes(x = 8, y = 7.9, xend = 2, yend = 1.5),
color = "black", curvature = -0.2, size = 1.5, alpha = 0.1) +
geom_curve(aes(x = 6, y = 4, xend = 2, yend = 1.5),
color = "black", curvature = -0.1, size = 1, alpha = 0.1) +
geom_curve(aes(x = 6, y = 8,
xend = 6.5, yend = 2.2),
color = "black", curvature = -0.1, size = 2, alpha = 0.1) +
geom_curve(aes(x = 8, y = 7.9,
xend = 6.5, yend = 2.2),
color = "black", curvature = -0.1, size = 0.8, alpha = 0.1) +
geom_curve(aes(x = 8, y = 3.4,
xend = 8, yend = 7.9),
color = "black", curvature = 0.1, size = 0.6, alpha = 0.1) +
geom_curve(aes(x = 9, y = 9,
xend = 6, yend = 4),
color = "black", curvature = -0.3, size = 1.5, alpha = 0.1) +
geom_curve(aes(x = 9, y = 9,
xend = 6, yend = 8),
color = "black", curvature = 0.3, size = 1.3, alpha = 0.1) +
geom_curve(aes(x = 7.3, y = 1,
xend = 6, yend = 8),
color = "black", curvature = 0.3, size = 0.5, alpha = 0.1)

Answer 1

Another option is to use different linetypes, these are generally more distinguishable than line thickness. This can be controlled with the linetype aesthetic