根据名称重复表格列 | 附Excel宽表示例（偏好data.table解法）

Alright, let's work through this problem—since you asked for a data.table solution first, that's what I'll lead with.

Step 1: Confirm the starting data #

First, let's reuse your data.table definition to keep things consistent:

library(data.table)
a <- data.table(names = c("product 1", "product 2"), "9-10" = c(1, 5), "21-23" = c(3, 2))

When printed, your initial wide-format table looks like this:

names 9-10 21-23
1: product 1    1     3
2: product 2    5     2

Step 2: Data.table solution (wide to long format) #

From your description, it sounds like you want to convert this wide table into a long format where each product-machine shift pair gets its own row (meaning the names values repeat for each shift column).

The melt() function in data.table is perfect for this task:

# Convert wide table to long format
a_long <- melt(a, 
               id.vars = "names",  # Keep this column as the repeating identifier
               variable.name = "machine_shift",  # Name for the new shift label column
               value.name = "capacity")          # Name for the capacity values column

Result of the code #

Running the above will give you this cleaned long-format table:

names machine_shift capacity
1: product 1        9-10        1
2: product 2        9-10        5
3: product 1       21-23        3
4: product 2       21-23        2

Quick code breakdown #

• id.vars = "names" tells melt() to retain the product names as the anchor that repeats across rows
• variable.name defines what to call the new column holding the shift labels ("9-10", "21-23")
• value.name names the column that stores the actual capacity numbers

Alternative: Tidyverse solution #

If you prefer using tidyverse tools, here's an equivalent approach with dplyr and tidyr:

library(tidyverse)
a_long_tidy <- a %>%
  pivot_longer(cols = -names, 
               names_to = "machine_shift", 
               values_to = "capacity")

This produces the exact same output as the data.table version—just a different syntax for your preferred workflow.

内容的提问来源于stack exchange，提问作者PavoDive