如何根据不同的类找到多少唯一的值

Question

我的数据是一组大数据。每个唯一ID包括一个或多个类，每个类包含一个或多个X的唯一值。但是，我们可能在不同的ID中有相同的类(例如，ID009和ID020有相同的类)，我试图根据不同的ID来找出每个类值X的唯一值。

ID <- c("ID004", "ID004", "ID004", "ID004", "ID004", "ID004", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID006", "ID009", "ID009", "ID009", "ID009", "ID009", "ID009", "ID009","ID020", "ID020", "ID020", "ID020", "ID020", "ID020", "ID020", "ID020", "ID023", "ID023", "ID023", "ID023", "ID023", "ID023","ID023", "ID023", "ID023", "ID023")
Class <- c("CMP-001", "CMP-001", "CMP-001", "CMP-001", "CMP-001","CMP-001", "CMP-001", "CMP-001", "CMP-001", "CMP-001", "CMP-001","CMP-001", "CMP-001", "CMP-001", "CMP-002", "CMP-002", "CMP-002","CMP-002", "CMP-002", "CMP-005", "CMP-005", "CMP-005", "CMP-002", "CMP-002", "CMP-002", "CMP-002", "CMP-002","CMP-002", "CMP-002", "CMP-002", "CMP-002", "CMP-002", "CMP-002", "CMP-002","CMP-002", "CMP-004", "CMP-004", "CMP-001", "CMP-001", "CMP-001", "CMP-001", "CMP-001","CMP-001", "CMP-001", "CMP-001", "CMP-001", "CMP-001")
X <- c(1,1,2,3,3,3,4,4,4,4,4,4,4,4,5,5,6,6,6,7,7,8,9,9,10,10,10,10,10,11,11,12,12,13,13,14,14,15,15,15,16,16,17,17,18,18,18)
data <- data.frame(ID, Class, X)

结果应该是；

ID         class       No. of X value
ID004     CMP-001           3
ID006     CMP-001           1
          CMP-002           2
          CMP-005           2
ID009     CMP-002           2
ID020     CMP-002           3
          CMP-004           1
ID023     CMP-001           4

谢谢你的帮助,

Answer 1

在这里，在使用“ID”、“类”进行分组之后，n_distinct是有用的。

library(dplyr)
data %>% 
   group_by(ID, Class) %>%
   summarise(No_X_value = n_distinct(X), .groups = 'drop')

-output

# A tibble: 8 x 3
#  ID    Class   No_X_value
#  <chr> <chr>        <int>
#1 ID004 CMP-001          3
#2 ID006 CMP-001          1
#3 ID006 CMP-002          2
#4 ID006 CMP-005          2
#5 ID009 CMP-002          2
#6 ID020 CMP-002          3
#7 ID020 CMP-004          1
#8 ID023 CMP-001          4

或使用data.table

library(data.table)
setDT(data)[, .(No_X_value = uniqueN(X), .(ID, Class)]

或者将base R与aggregate结合使用

aggregate(X ~ ., unique(data), FUN = length)
#     ID   Class X
#1 ID004 CMP-001 3
#2 ID006 CMP-001 1
#3 ID023 CMP-001 4
#4 ID006 CMP-002 2
#5 ID009 CMP-002 2
#6 ID020 CMP-002 3
#7 ID020 CMP-004 1
#8 ID006 CMP-005 2

Answer 2

您还可以在base R中使用像这样的aggregate()方法

#Code
df <- aggregate(X~ID+Class,data,function(x) length(unique(x)))

输出：

     ID   Class X
1 ID004 CMP-001 3
2 ID006 CMP-001 1
3 ID023 CMP-001 4
4 ID006 CMP-002 2
5 ID009 CMP-002 2
6 ID020 CMP-002 3
7 ID020 CMP-004 1
8 ID006 CMP-005 2

Answer 3

如果你使用基数R，我认为aggregate @akrun的方法已经是一个非常有效的方法了。下面是另一个选择，但更复杂。

subset(as.data.frame(xtabs(cnt ~ ID + Class,cbind(cnt = 1,unique(data)))),Freq >0)

这给

      ID   Class Freq
1  ID004 CMP-001    3
2  ID006 CMP-001    1
5  ID023 CMP-001    4
7  ID006 CMP-002    2
8  ID009 CMP-002    2
9  ID020 CMP-002    3
14 ID020 CMP-004    1
17 ID006 CMP-005    2