How to compute quantiles in the R programming language. More details: [ Ссылка ]
R code of this video:

set.seed(15051) # Set seed for reproducibility
x ＜- round(runif(1000, 0, 100)) # Create uniformly distributed data
x # Print data to RStudio console

quantile(x) # Apply quantile function

x_NA ＜- c(x, NA) # Create example data with NA

quantile(x_NA) # Apply quantile function to NA vector

quantile(x_NA, na.rm = TRUE) # Use na.rm argument

unname(quantile(x)) # Get only the quantile values

data(iris) # Load Iris data
head(iris) # Head of Iris data

# The dplyr package is not needed. This was a little mistake I made at 04:00 in the video.
# install.packages("dplyr") # Install dplyr package
# library("dplyr") # Load dplyr package

do.call("rbind",
tapply(iris$Sepal.Length, # Specify numeric column
iris$Species, # Specify group variable
quantile))

quantile(x, probs = 0.5) # Median

quantile(x, probs = seq(0, 1, 1/3)) # Tertiles

quantile(x, probs = seq(0, 1, 1/4)) # Quartiles

quantile(x, probs = seq(0, 1, 1/5)) # Quintiles

quantile(x, probs = seq(0, 1, 1/6)) # Sextiles

quantile(x, probs = seq(0, 1, 1/7)) # Septiles

quantile(x, probs = seq(0, 1, 1/8)) # Octiles

quantile(x, probs = seq(0, 1, 1/10)) # Deciles

quantile(x, probs = seq(0, 1, 1/12)) # Duo-deciles or dodeciles

quantile(x, probs = seq(0, 1, 1/16)) # Hexadeciles

quantile(x, probs = seq(0, 1, 1/20)) # Ventiles, vigintiles, or demi-deciles

quantile(x, probs = seq(0, 1, 1/100)) # Percentiles

quantile(x, probs = seq(0, 1, 1/1000)) # Permilles or milliles

y ＜- x + rnorm(1000, 0, 30) # Create y-data

qqplot(x, y) # Quantile-Quantile plot of x & y

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