Part 1: Facet_wrap
install.packages("ggplot2")
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.5'
## (as 'lib' is unspecified)
library(ggplot2)
ggplot(diamonds, aes(x = price, fill = cut)) +
geom_histogram(bins = 20, color = "red", alpha = 0.6) +
facet_wrap(~ cut) +
labs(
title = "Distribution of Diamond Prices by Cut",
x = "Price (USD)",
y = "Count"
) +
scale_fill_brewer(palette = "Set2") +
theme_minimal()
Facet_grid
ggplot(diamonds, aes(x = carat, y = price, color = cut)) +
geom_point(alpha = 0.7) +
facet_grid(cut ~ color) +
labs(
title = "Diamond Price vs Carat by Cut and Color",
x = "Carat",
y = "Price (USD)",
color = "Cut Quality"
) +
scale_color_brewer(palette = "Dark2") +
theme_minimal()
Part 2:
library(ggplot2)
install.packages("patchwork")
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.5'
## (as 'lib' is unspecified)
library(patchwork)
Scatterplot
#scatterplot
p1 <- ggplot(diamonds, aes(x = carat, y = price, color = cut)) +
geom_point(alpha = 0.6) +
labs(title = "Carat vs Price") +
theme_minimal()
#barplot
p2 <- ggplot(diamonds, aes(x = cut, fill = cut)) +
geom_bar() +
labs(title = "Count of Diamonds by Cut", x = "Cut", y = "Count") +
theme_minimal()
#density plot
p3 <- ggplot(diamonds, aes(x = price, fill = cut)) +
geom_density(alpha = 0.5) +
labs(title = "Price Distribution by Cut") +
theme_minimal()
#boxplot
p4 <- ggplot(diamonds, aes(x = cut, y = price, fill = cut)) +
geom_boxplot() +
labs(title = "Price by Cut") +
theme_minimal()
#combining the plots
# Combine plots
combined_plot <- (p1 | p2) / (p3 | p4) +
plot_layout(guides = "collect") &
theme(legend.position = "bottom")
combined_plot
#PNG (300 dpi)
ggsave(
filename = "combined_figure.png",
plot = combined_plot,
width = 10,
height = 8,
dpi = 300
)
ggsave(
filename = "combined_figure.pdf",
plot = combined_plot,
width = 10,
height = 8
)
write.csv(diamonds, "diamonds_data.csv", row.names = FALSE)