问题
How can we transform data of the form
df <- structure(list(customer_number = c(3, 3, 1, 1, 3),
item = c("milkshake","burger", "apple", "burger", "water")
),
row.names = c(NA, -5L), class = "data.frame")
# customer_number item
# 1 3 milkshake
# 2 3 burger
# 3 1 apple
# 4 1 burger
# 5 3 water
into numerically encoded dummy variables, like this
data.frame(customer_number=c(1,3),
item_milkshake=c(0,1),
item_burger=c(1,1),
item_apple=c(1,0),
item_water=c(0,1))
# customer_number item_milkshake item_burger item_apple item_water
# 1 1 0 1 1 0
# 2 3 1 1 0 1
回答1:
We can create a dummy column with value as 1 and get the data in wide format.
library(dplyr)
df %>%
mutate(n = 1) %>%
arrange(customer_number) %>%
tidyr::pivot_wider(names_from = item, values_from = n,
values_fill = list(n = 0), names_prefix = "item_")
# A tibble: 2 x 5
# customer_number item_apple item_burger item_milkshake item_water
# <dbl> <dbl> <dbl> <dbl> <dbl>
#1 1 1 1 0 0
#2 3 0 1 1 1
回答2:
If you want to use basic R functions, here is a simple solution using table() function:
#Create the dataset
df <- structure(list(customer_number = c(3, 3, 1, 1, 3), item = c("milkshake",
"burger", "apple", "burger", "water")), row.names = c(NA, -5L
res <- as.matrix(table(df$customer_number,df$item))
res[res > 0 ] <- 1 #dummy variable
res
apple burger milkshake water
1 1 1 0 0
3 0 1 1 1
You can add customer_number as a separate column to the matrix:
res <- cbind(customer_number = as.numeric(rownames(res)), res)
res
customer_number apple burger milkshake water
1 1 1 1 0 0
3 3 0 1 1 1
来源:https://stackoverflow.com/questions/60427257/create-numerically-encoded-dummy-variables-efficiently-in-r