library("ggplot2")
data(diamonds)
ggplot(data = diamonds, aes(x = cut, y = price)) +
scale_fill_manual (values = c("#d53e4f",
"#f46d43", "#66c2a5", "#3288bd", "#9970ab")) +
scale_color_manual(values = c("#d53e4f", "#f46d43",
"#66c2a5", "#3288bd",
"#9970ab")) +
geom_jitter(aes(color = cut), size = .01, alpha = 0.4, show.legend = FALSE) +
geom_violin(aes(fill = cut), alpha = 0.5, color = NA) +
geom_boxplot(aes(color = cut), alpha = 0.5, show.legend = FALSE) +
xlab("\nCut") +
ylab("Price") +
labs(title="\nDiamonds", subtitle ="", caption = "Data: diamonds\n", fill= "Cut") +
theme(
axis.text.x = element_text(size = 12),
axis.text.y = element_text (size = 12),
axis.title.x = element_text (size = 13, face="bold"),
axis.title.y = element_text(size = 13, face="bold"),
panel.spacing = unit(0, "pt"),
panel.border = element_blank(),
panel.grid.major.x = element_blank(),
strip.background = element_blank(),
strip.text = element_text(colour = "black"),
legend.justification = c("right", "top"),
legend.box.just = "right",
legend.margin = margin(6, 6, 6, 6),
plot.title = element_text(size = 20, face = "bold", hjust = 0.5),
plot.subtitle = element_text(size = 16, face = "bold", hjust = 0.5),
plot.caption = element_text(size = 10, face = "bold", hjust = 1),
panel.background = element_rect(fill="white", colour="white")
)
This time we work with diamond data. It generates a diagram of box with “ggplot2”, with various details in the chart that allow better perceive the distribution of data.