R DPLYR计数值BY组

Question

HAVE = data.frame(  STUDENT =c( 1,1,2,2,2,3,3   ),
TEST    =c( 'A','B','A','B','C','A','C' ))
WANT = data.frame(STUDENT=c(1,2,3),
A=c(1,1,1),
B=c(1,1,0),
C=c(0,1,1),
TOT=c(2,3,2),
TOT.NOT.A=c(1,2,1))

我有一个垂直数据，并希望转换为水平数据，如上所示。我可以做

WANT = HAVE %>% group_by(STUDENT) %>% mutate(TOT = n_distinct (TEST)) 

获得"TOT"，但我不知道如何获得"A"、"B"、"C"或"TOT。不是。

Answer 1

我们可以用pivot_wider将其重塑为"宽"格式；TOT"；al柱

library(dplyr)
library(tidyr)
HAVE %>% 
pivot_wider(names_from = TEST, values_from = TEST,
values_fn = length, values_fill = 0) %>% 
mutate(TOT = rowSums(across(-STUDENT), na.rm = TRUE),
TOT_NOT_A = rowSums(across(B:C), na.rm = TRUE))

-输出

# A tibble: 3 × 6
STUDENT     A     B     C   TOT TOT_NOT_A
<dbl> <int> <int> <int> <dbl>     <dbl>
1       1     1     1     0     2         1
2       2     1     1     1     3         2
3       3     1     0     1     2         1

---

或使用base R

out <- addmargins(table(HAVE), 2)
cbind(out, TOT_NOT_A = rowSums(out[, c("B", "C")]))
A B C Sum TOT_NOT_A
1 1 1 0   2         1
2 1 1 1   3         2
3 1 0 1   2         1

Answer 2

这里有一种将rowwise与c_across和sum相结合的替代方法：

library(dplyr)
HAVE %>% 
add_count(STUDENT, TEST) %>% 
pivot_wider(names_from = TEST, values_from =n, values_fill = 0 ) %>% 
rowwise() %>% 
mutate(TOT = sum(c_across(A:C), na.rm = TRUE),
TOT_NOT_A = sum(c_across(B:C), na.rm = TRUE))

STUDENT     A     B     C   TOT TOT_NOT_A
<dbl> <int> <int> <int> <int>     <int>
1       1     1     1     0     2         1
2       2     1     1     1     3         2
3       3     1     0     1     2         1