data.table：拆分列，然后从宽格式到长格式[重复]

Question

我有以下格式的数据（摘录）：

# install.packages("data.table")
# install.packages("tidyverse")

library("data.table")
library("tidyverse")

dt <- data.table(
 date = lubridate::as_date(c("2021-01-01", "2021-01-02", "2021-01-03", "2021-01-04")),
 location = c("Westpark", "Northpark", "Estpark", "Southpark"),
 'receiver_a: max' = c(20, 30, 25, 15),
 'receiver_a: min' = c(10, 15, 20, 5),
 'receiver_b: max' = c(15, 45, 10, 50),
 'receiver_b: min' = c(15, 45, 10, 50)
)

> dt
        date  location receiver_a: max receiver_a: min receiver_b: max receiver_b: min
1: 2021-01-01  Westpark              20              10              15              15
2: 2021-01-02 Northpark              30              15              45              45
3: 2021-01-03   Estpark              25              20              10              10
4: 2021-01-04 Southpark              15               5              50              50

我现在想拆分列名中以receiver_...开头的所有列，并将它们转换为长格式：

• 将列名中带有receiver_...的所有列拆分为新列 列receiver、max 和min。以receiver... 开头的“旧”列名称中: 之后的所有内容都用于新列名称，此处为max 和min。
• 新栏目 receiver 包含例如receiver_a、receiver_b 等作为值。新列 max 和 min 包含各自的数值。

这可以用tidyr::pivot_longer()实现：

# dt <-  dt %>% 
dt %>%
  tidyr::pivot_longer(
    cols         = dplyr::contains(":"),
    names_to     = c("receiver", ".value"),
    names_sep    = ": ", 
    names_repair = "minimal"
  )

# A tibble: 8 x 5
  date       location  receiver     max   min
  <date>     <chr>     <chr>      <dbl> <dbl>
1 2021-01-01 Westpark  receiver_a    20    10
2 2021-01-01 Westpark  receiver_b    15    15
3 2021-01-02 Northpark receiver_a    30    15
4 2021-01-02 Northpark receiver_b    45    45
5 2021-01-03 Estpark   receiver_a    25    20
6 2021-01-03 Estpark   receiver_b    10    10
7 2021-01-04 Southpark receiver_a    15     5
8 2021-01-04 Southpark receiver_b    50    50

• cols = dplyr::contains(":")：选择名称中带有:的所有列，例如receiver_a: max
• names_to = c("receiver", ".value")：将选定的列拆分为receiver 和.value。 .value 表示名称的组成部分定义了包含单元格值的列的名称
• names_sep = ": " 如果names_to 包含多个值，则这些参数控制列名的拆分方式，此处为: （冒号后的空格）

我的问题：这也可以通过（更快的）data.table 解决方案（例如使用melt()）来完成吗？

Answer 1

我们可以在data.table 中使用measure 和patterns

library(data.table)
nm1 <- unique(sub(":.*", "", names(dt)[-(1:2)]))
melt(dt, measure = patterns("max", "min"),
    value.name = c("max", "min"), variable.name = "receiver")[, 
     receiver := nm1[receiver]][]

-输出

         date  location   receiver max min
1: 2021-01-01  Westpark receiver_a  20  10
2: 2021-01-02 Northpark receiver_a  30  15
3: 2021-01-03   Estpark receiver_a  25  20
4: 2021-01-04 Southpark receiver_a  15   5
5: 2021-01-01  Westpark receiver_b  15  15
6: 2021-01-02 Northpark receiver_b  45  45
7: 2021-01-03   Estpark receiver_b  10  10
8: 2021-01-04 Southpark receiver_b  50  50