旋轉多列R

我有這個資料：

    structure(list(classificador = c("classificador 1", "classificador 1", 
"classificador 1", "classificador 1", "classificador 1", "classificador 2", 
"classificador 2", "classificador 2", "classificador 2", "classificador 2", 
"classificador 3", "classificador 3", "classificador 3", "classificador 3", 
"classificador 3"), classe = structure(c(1L, 2L, 3L, 4L, 5L, 
1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L), .Label = c("bolha", 
"coral_sol", "cosc_mult", "coscinodiscus", "detritus", "fake_coral", 
"multiples", "org_parts", "organism", "shadow"), class = "factor"), 
    media_entrou = c(0.000181463342477325, 9.11739514644428e-06, 
    0, 0.00710836752524651, 0.0523307152250179, 5.76207054303695e-05, 
    2.31948309497038e-05, 0.000533722409264464, 0.00395244621833009, 
    0.0277347189726644, 0.000511091116817504, 2.78792287970657e-05, 
    0.00167363838758039, 0.00714582937886204, 0.03664291179572
    ), desv_pad_entrou = c(0.000625138593404583, 4.01259397230609e-05, 
    0, 0.00982865377212798, 0.0382102106478645, 0.000197304670837601, 
    0.00015803336539453, 0.00133833325218429, 0.00460178168250652, 
    0.0198204066019173, 0.00560789561914724, 0.000295803787791627, 
    0.0011439791450099, 0.00660048491487252, 0.023022755540947
    ), media_saiu = c(6.31000967592145e-05, 0, 0, 0.0117956025289566, 
    0.00890647892432332, 0.000100059064539586, 0, 0, 0.0587231357033222, 
    0.0639343116405082, 0.00028538070772188, 0, 2.54448072255982e-05, 
    0.0616763969528522, 0.0284492872735916), desv_pad_saiu = c(0.00010828405298676, 
    0, 0, 0.00782886688427178, 0.00460945360308487, 0.000418014988563, 
    0, 0, 0.0258394941887122, 0.0678523075381303, 0.000824409079665752, 
    0, 0.000147663248976053, 0.0346114091736888, 0.0165290142815091
    ), N_ciclos = c(118L, 118L, 118L, 118L, 118L, 318L, 318L, 
    318L, 318L, 318L, 158L, 158L, 158L, 158L, 158L)), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -15L), groups = structure(list(
    classificador = c("classificador 1", "classificador 2", "classificador 3"
    ), .rows = structure(list(1:5, 6:10, 11:15), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -3L), .drop = TRUE))

我想用新的列來透視這些資料：classificador, classe, E_S, media, 和desvio。其中E_S列有值名稱entrou相應的列media_entrou和desvio_entrou和值名稱saiu相應的列media_saiu和desvio_saiu和列值media_entrou和media_saiu新列media和列值desvio_entrou和desvio_saiu新列desvio。

前 4 行的預期輸出：

謝謝

uj5u.com熱心網友回復：

我們可以使用pivot_longer，指定正則運算式模式來捕獲組，names_pattern即^([^_] )匹配一個或多個不是_來自開始 ( ^) 和捕獲 ( (...))_的字符，然后捕獲.*來自列名的其余字符 ( ) ，這將是'E_S' 列中的值

library(tidyr)
library(dplyr)
library(stringr)
df1 %>% 
   ungroup %>% 
   select(-N_ciclos) %>%
   dplyr::rename_with(~ str_remove(., "_pad")) %>% 
   pivot_longer(cols = contains("_"), names_to = c(".value", "E_S"),
      names_pattern = "^([^_] )_(.*)")

-輸出

# A tibble: 30 × 5
   classificador   classe        E_S         media      desv
   <chr>           <fct>         <chr>       <dbl>     <dbl>
 1 classificador 1 bolha         entrou 0.000181   0.000625 
 2 classificador 1 bolha         saiu   0.0000631  0.000108 
 3 classificador 1 coral_sol     entrou 0.00000912 0.0000401
 4 classificador 1 coral_sol     saiu   0          0        
 5 classificador 1 cosc_mult     entrou 0          0        
 6 classificador 1 cosc_mult     saiu   0          0        
 7 classificador 1 coscinodiscus entrou 0.00711    0.00983  
 8 classificador 1 coscinodiscus saiu   0.0118     0.00783  
 9 classificador 1 detritus      entrou 0.0523     0.0382   
10 classificador 1 detritus      saiu   0.00891    0.00461  
# … with 20 more rows

標籤：r dplyr 枢 整理

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