library(ggridges)
ggplot(diamonds, aes(x = price, y = cut, fill = cut)) +
geom_density_ridges() +
theme_ridges() +
theme(legend.position = "none")
library(ggridges)
data1 <- read.table("Datas/probly.csv", header=TRUE, sep=",")
data1 <- data1 %>%
gather(key="text", value="value") %>%
mutate(text = gsub("\\.", " ",text)) %>%
mutate(value = round(as.numeric(value),0)) %>%
filter(text %in% c("Almost Certainly","Very Good Chance","We Believe","Likely","About Even", "Little Chance", "Chances Are Slight", "Almost No Chance"))
# Plot
data1 %>%
mutate(text = fct_reorder(text, value)) %>%
ggplot( aes(y=text, x=value, fill=text)) +
geom_density_ridges(alpha=0.6, stat="binline", bins=20) +
theme_ridges() +
theme(
legend.position="none",
panel.spacing = unit(0.1, "lines"),
strip.text.x = element_text(size = 8)
) +
xlab("") +
ylab("Assigned Probability (%)")
library(ggridges)
ggplot(lincoln_weather, aes(x = `Mean Temperature [F]`, y = `Month`, fill = ..x..)) +
geom_density_ridges_gradient(scale = 3, rel_min_height = 0.01) +
scale_fill_viridis(name = "Temp. [F]", option = "C") +
labs(title = 'Temperatures in Lincoln NE in 2016') +
theme_ipsum() +
theme(
legend.position="none",
panel.spacing = unit(0.1, "lines"),
strip.text.x = element_text(size = 8)
)
