r - 如何使用数据框中的当前行值检查前一行值

Question

如何通过对特定 ID 进行分组，为数据框的所有列动态检查前一行值和当前行值。

我的数据框:

ID  ITEM1     ITEM2    ITEM3           
  1    A         A        A     
  2    C         B        C       
  1    A         B        C
  1    B         A        C    
  2    NA        B        F      
  3    A         A        D     
  4    R         G        J 
  4    H         T        J

例如:

ID  ITEM1     ITEM2    ITEM3    ITEM1change  ITEM2change   ITEM3change                   
  1    A         A        A       0            0             0          
  1    A         B        C       0            1             1
  1    B         A        C       1            1             0 
  2    C         B        C       0            0             0
  2    NA        B        F       1            0             1
  3    A         A        D       0            0             0
  4    R         G        J       0            0             0
  4    H         T        J       1            1             0

我的最终输出将是:

  Fiels         modifiedcout   unmodifiedcount Total      
  ITEM1change     3               5              8                
  ITEM2change     3               5              8    
  ITEM3change     2               6              8

我的数据:

structure(list(ID = c(1, 2, 1, 1, 2, 3, 4, 4), ITEM1 = structure(c(1L, 
3L, 1L, 2L, NA, 1L, 5L, 4L), .Label = c("A", "B", "C", "H", "R"
), class = "factor"), ITEM2 = structure(c(1L, 2L, 2L, 1L, 2L, 
1L, 3L, 4L), .Label = c("A", "B", "G", "T"), class = "factor"), 
    ITEM3 = structure(c(1L, 2L, 2L, 2L, 4L, 3L, 5L, 5L), .Label = c("A", 
    "C", "D", "F", "J"), class = "factor")), .Names = c("ID", 
"ITEM1", "ITEM2", "ITEM3"), row.names = c(NA, -8L), class = "data.frame")

Answer 1

一个可能的解决方案:

library(dplyr)
library(tidyr)

df %>% 
  gather(item, value, -1) %>% 
  group_by(ID, item) %>% 
  mutate(change = lag(value, default = first(value)) != value,
         change = replace(change, is.na(change), TRUE)) %>% 
  group_by(item) %>% 
  summarise(modified = sum(change, na.rm = TRUE),
            unmodified = sum(!change, na.rm = TRUE)) %>% 
  mutate(total = modified + unmodified)

这使:

# A tibble: 3 x 4
   item modified unmodified total
  <chr>    <int>      <int> <int>
1 ITEM1        3          5     8
2 ITEM2        3          5     8
3 ITEM3        2          6     8