将宽 table 转换为长 table 选择带有 "start_with" 的列

Question

我有一个 table 看起来像这样：

Z1	R1	Z2	R2	...	Z100	R100
1246	1	2986	3	...	3163	4
2734	5	1066	7	...	2645	8

它是一个宽 table，我想将其转换成这样的长 table：

Z	时间（毫秒）	R	反应
Z1	1246	R1	1
Z1	2734	R1	5
Z2	2986	R2	3
Z2	1066	R2	7
...	...	...	...
Z100	3163	R100	4
Z100	2645	R100	8

我试过这个：

data_time_config_long <- data_time_config %>%
  gather(key = "Z", value = "Time in ms", select(data_time_config, starts_with('Z'))) %>%
  gather(key = "R", value = "Reaction", select(data_time_config, starts_with('R')))

我收到这个错误：

Error: Must subset columns with a valid subscript vector. x Subscript has the wrong type `tbl_df< Z1 : double Z2 : double Z3 : double Z4 : double Z5 : double Z6 : double Z7 : double Z8 : double Z9 : double Z10 : double Z11 : double Z12 : double Z13 : double Z14 : double Z15 : double Z16 : double Z17 : double Z18 : double Z19 : double Z20 : double Z21 : double Z22 : double Z23 : double Z24 : double Z25 : double Z26 : double Z27 : double Z28 : double Z29 : double Z30 : double Z31 : double Z32 : double Z33 : double Z34 : double Z35 : double Z36 : double Z37 : double Z38 : double Z39 : double Z40 : double Z41 : double Z42 : double Z43 : double Z44 : double Z45 : double Z46 : double Z47 : double Z48 : double Z49 : double Z50 : double Z51 : double Z52 : double Z53 : double Z54 : double Z55 : double Z56 : double Z57 : double Z58 : double Z59 : double Z60

我做错了什么？

Answer 1

我认为这个问题不能直接用 tidyr::gather() 解决，它已被弃用，应该使用 tidyr::pivot_longer()。我的方法是这样的：

library(tidyverse)

#dummy data
df <- data.frame(Z1 = c(1246,2734), R1 = c(1,5), 
                 Z2 = c(2986,1066), R2 = c(3,7),
                 Z100 = c(3163,2645), R100 = c(4,8))

# intermediate data.frame
idf <- df %>%
   # add row numbers as we need them to keep the order
  dplyr::mutate(rn = dplyr::row_number()) %>%
  # gather is depricated
  tidyr::pivot_longer(-rn, names_to = "colu", values_to = "vals") %>%
  # extract number from the column names that now are a column as we need them to keep the order also
  dplyr::mutate(nr = readr::parse_number(colu))

# select columns with Z and join columns with R acording to row number and numeric part of column names
idf %>%
  dplyr::filter(stringr::str_detect(colu, "Z")) %>%
  dplyr::left_join(idf %>%
                     dplyr::filter(stringr::str_detect(colu, "R")), by = c("rn", "nr")) %>%
  # order to get the exact output you are looking for
  dplyr::arrange(nr) %>%
  # select and rename to get exactout put you a looking vor
  dplyr::select(Z = colu.x, `Time in ms` = vals.x, R = colu.y, Reaction = vals.y) 

# A tibble: 6 x 4
  Z     `Time in ms` R     Reaction
  <chr>        <dbl> <chr>    <dbl>
1 Z1            1246 R1           1
2 Z1            2734 R1           5
3 Z2            2986 R2           3
4 Z2            1066 R2           7
5 Z100          3163 R100         4
6 Z100          2645 R100         8

Answer 2

另一种方式：

df <- data.frame(Z1 = c(1246,2734), R1 = c(1,5), 
                 Z2 = c(2986,1066), R2 = c(3,7),
                 Z100 = c(3163,2645), R100 = c(4,8))

library(dplyr)
df |> 
  tidyr::pivot_longer(everything(), names_to = c(".value", "Ind"), names_pattern = "(.)(\d.*)") |> 
  rename(`Time in ms` = Z, Reaction = R) |> 
  mutate(Z = paste0("Z", Ind), R = paste0("R", Ind)) |> 
  select(Z, `Time in ms`, R, Reaction)

# A tibble: 6 x 4
  Z     `Time in ms` R     Reaction
  <chr>        <dbl> <chr>    <dbl>
1 Z1            1246 R1           1
2 Z2            2986 R2           3
3 Z100          3163 R100         4
4 Z1            2734 R1           5
5 Z2            1066 R2           7
6 Z100          2645 R100         8

将宽 table 转换为长 table 选择带有 "start_with" 的列

Convert wide table into long table selecting columns with "start_with"

r

dataframe

tidyr