Draw Normal, Left & Right Skewed Distributions (2 Examples) | ggplot2 Density Plot | tidyr Package

Описание: How to plot normal, left, and right skewed densities in the R programming language. More details: https://statisticsglobe.com/draw-norm...
R code of this video:

set.seed(35486) # Create random distributions
data ＜- data.frame(x1 = rbeta(1000, 10, 2),
x2 = rbeta(1000, 5, 2),
x3 = rnorm(1000),
x4 = rbeta(1000, 2, 5),
x5 = rbeta(1000, 2, 10))

plot(density(data$x1), col = 2, # Overlay all columns as densities
xlim = c(- 3, 3),
ylim = c(0, 5))
lines(density(data$x2), col = 3)
lines(density(data$x3), col = 4)
lines(density(data$x4), col = 5)
lines(density(data$x5), col = 6)
legend("topleft", # Add legend to plot
legend = c("x1 = rbeta(1000, 10, 2)",
"x2 = rbeta(1000, 5, 2)",
"x3 = rnorm(1000)",
"x4 = rbeta(1000, 2, 5)",
"x5 = rbeta(1000, 2, 10)"),
col = 2:6,
lty = 1,
cex = 0.8)

install.packages("tidyr") # Install & load tidyr
library("tidyr")

data_long ＜- data %＞% # Convert wide to long data
pivot_longer(colnames(data)) %＞%
as.data.frame()

install.packages("ggplot2") # Install ggplot2 package
library("ggplot2") # Load ggplot2 package

ggplot(data_long, # Draw all densities in ggplot2 plot
aes(value,
fill = name)) +
geom_density(alpha = 0.25)

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