Язык R Отчет (Скворцов) / Анализ данных на языке R

# step 6 group_by

diamonds <- as_data_frame(diamonds) gr_diamonds <- group_by(diamonds, cut)

sample_n(diamonds, 2) slice(diamonds, 1)

sample_n(gr_diamonds, 2)

slice(gr_diamonds, 1)

# step 7 group_by and summarise ?summarise()

summarise(gr_diamonds, numbers = n(),

mean_price = mean(price), mean_x = mean(x), median_y = median(y), min_y = min(y))

# step 8

gr_diamonds <- group_by(diamonds, cut, color) summarise(gr_diamonds,

numbers = n(), mean_price = mean(price), mean_x = mean(x), median_y = median(y), min_y = min(y))

summarise(gr_diamonds,

numbers = n(), mean_price = mean(price), mean_x = mean(x), median_y = median(y), min_y = min(y),

great_price = sum(price > 5000))

# step 9

gr_mtcars <- group_by(mtcars, am, vs)

my_means <- summarise_all(gr_mtcars, funs(mean))

15. Data.table

# step 1 fread function

library(data.table)

system.time(fread("products.csv")) system.time(read.table("products.csv", header = T, sep = ";"))

products <- fread("products.csv")

# step 2 data.table vs dataframe products[1:10, ]

products[products$price > 10000, ]

with(iris, iris[Species == "virginica", ]) #iris$Species

products[price > 10000]

products[(price > 1000) &

(brand %in% c("Epson", "Apple"))]

# step 3 data filtering

products[available, ] products[available == TRUE, ]

list(price.1k = paste0(price / 1000, " тыс.руб"))]$price.1k

products[, list(name, price)] products[, .(name, price)]

products[, c("name", "price"), with = F]

products[order(-price), .(name = head(name), price = head(price))]

products[, .(price = sum(price))]

a <- products[, list(name.with.brand = paste0(brand, " - ", name))]

a[order(name.with.brand)]

products[, list(name.with.brand = paste0(brand, " - ", name))][order(name.with.brand)]

products[, .(price = { a <- mean(price)

b <- median(price) c(min(price), max(price), a/b)

})]

library(data.table)

products <- fread("products.csv", colClasses = c(price = "double"))