Question

我有一个data.table，如下所示：

>DT
   ID Year Value ABC_1 ABC_2 ABC_3
1:  3 2015     5     0     1     0
2:  4 2015     2     1     0     1
3:  5 2015     1     0     1     1

我想为每个ABC _...做的是：

> unique(DT[Year == 2015 & ABC_1 == 1, .(Year = Year, ABC = ABC_1, N = .N, MEAN = mean(Value))])
   Year ABC N MEAN
1: 2015   1 1    2
> unique(DT[Year == 2015 & ABC_2 == 1, .(Year = Year, ABC = ABC_2, N = .N, MEAN = mean(Value))])
   Year ABC N MEAN
1: 2015   1 2    3
> unique(DT[Year == 2015 & ABC_3 == 1, .(Year = Year, ABC = ABC_3, N = .N, MEAN = mean(Value))])
   Year ABC N MEAN
1: 2015   1 2  1.5

我有超过20列的ABC _...我想把这个语句放在for循环中。我的问题是选择/规则需要列名。它无效：

> abc_name <- names(DT)[names(DT) %like% 'ABC']
> abc_name
[1] "ABC_1" "ABC_2" "ABC_3"
> abc_row<- data.table(Year=0, ABC=0, N=0, MEAN=0)
> for (i in 1: length(abc_name)){
+   
+   temp_row <- unique(DT[Year == 2015 & abc_name[i] == 1, .(Year = Year, ABC = abc_name[i], N = .N, MEAN = mean(Value))])
+   abc_row <- rbind(abc_row, temp_row)
+ }
> abc_row
   Year ABC N MEAN
1:    0   0 0    0

temp_row为空... 当我使用abc_name[I]更改ABC_1时，它可以正常运行：

> abc_name <- names(DT)[names(DT) %like% 'ABC']
> abc_name
[1] "ABC_1" "ABC_2" "ABC_3"
> abc_row<- data.table(Year=0, ABC=0, N=0, MEAN=0)
> for (i in 1: length(abc_name)){
+ 
+   temp_row <- unique(DT[Year == 2015 & ABC_1 == 1, .(Year = Year, ABC = ABC_1, N = .N, MEAN = mean(Value))])
+   abc_row <- rbind(abc_row, temp_row)
+ }
> abc_row
   Year ABC N MEAN
1:    0   0 0    0
2: 2015   1 1    2
3: 2015   1 1    2
4: 2015   1 1    2

如何在我的脚本工作的for循环中使用abc_name？我希望你理解我的问题，有人可以帮助我。

Answer 1

使用lapply循环遍历名称向量（＆＃39; abc_name＆＃39;），在OP的帖子中应用逻辑，获取get列的值和rbind list元素。{/ p>

lst <- lapply(abc_name, function(nm)
          unique(DT[Year == 2015 & get(nm) == 1,
          .(Year = Year, ABC = get(nm), N = .N, MEAN = mean(Value))]))

rbindlist(lst)
#   Year ABC N MEAN
#1: 2015   1 1  2.0
#2: 2015   1 2  3.0
#3: 2015   1 2  1.5

或另一个选项是melt来重塑广泛的＆＃39;长期＆＃39;格式，按＆变量＆＃39;分组和＆＃39;年＆＃39;，并在＆＃39; i＆＃39;中指定逻辑索引。（value==1），总结数据集

melt(DT, measure = abc_name)[value==1, .(ABC=1, N= .N, 
     MEAN= mean(Value)), .(variable, Year)][, variable := NULL][]
#   Year ABC N MEAN
#1: 2015   1 1  2.0
#2: 2015   1 2  3.0
#3: 2015   1 2  1.5

R data.table规则，列名为字符串

1 个答案: