我有一个有4列的data.table dat，例如(col1，col2，col3和col4)。
输入数据:
structure(list(col1 = c(5.1, 5.1, 4.7, 4.6, 5, 5.1, 5.1, 4.7,
4.6, 5), col2 = c(3.5, 3.5, 3.2, 3.1, 3.6, 3.5, 3.5, 3.2, 3.1,
3.6), col3 = c(1.4, 1.4, 1.3, 1.5, 1.4, 3.4, 3.4, 1.3, 1.5, 1.4
), col4 = structure(c(1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L), .Label = c("setosa",
"versicolor", "virginica", "eer"), class = "factor")), .Names = c("col1",
"col2", "col3", "col4"), row.names = c(NA, -10L), class = c("data.table",
"data.frame"))
r
col1 col2 col3 col4
1: 5.1 3.5 1.4 setosa
2: 5.1 3.5 1.4 setosa
3: 4.7 3.2 1.3 setosa
4: 4.6 3.1 1.5 setosa
5: 5.0 3.6 1.4 setosa
6: 5.1 3.5 3.4 eer
7: 5.1 3.5 3.4 eer
8: 4.7 3.2 1.3 eer
9: 4.6 3.1 1.5 eer
10: 5.0 3.6 1.4 eer
我对
col3的每个唯一值在col4上执行以下操作dat[ , r_new:= sum(col3, na.rm = T), .(col4)] #syntax 1
因此，在sytnax上方创建一个新列
r_new，其值是通过添加那些col3相同的col4值获得的。因此，col4的每个唯一值在r_new列中将具有唯一值。我现在想要做的是与上面相同，但是不包括那些
col1和col2取相同值的行(如下所示)dat[col1 is different OR col2 is different , r_new:= sum(col3, na.rm = T), .(col4)]
在对行执行
sum功能时，它将执行的操作将不包括col1和col2都采用相同值的那些行。如何以与1相同的语法包含此条件？
预期产量:
col1 col2 col3 col4 r_new
1: 5.1 3.5 1.4 setosa 5.6
2: 5.1 3.5 1.4 setosa 5.6
3: 4.7 3.2 1.3 setosa 5.6
4: 4.6 3.1 1.5 setosa 5.6
5: 5.0 3.6 1.4 setosa 5.6
6: 5.1 3.5 3.4 eer 7.6
7: 5.1 3.5 3.4 eer 7.6
8: 4.7 3.2 1.3 eer 7.6
9: 4.6 3.1 1.5 eer 7.6
10: 5.0 3.6 1.4 eer 7.6
正如您在预期输出中看到的那样，对于
setosa第1和2行，其col1和col2具有相同的值，对于err第6和7行，其col1和col2，具有相同的值，因此我们没有添加这些行(我们只考虑了它们一次)。不用担心col3(如果col1和col2取相同的值，它将取相同的值。编辑:第二个目标:
structure(list(col1 = c(5.1, 5.1, 4.7, 4.6, 5, 5.1, 5.1, 4.7,
4.6, 5.1), col2 = c(3.5, 3.5, 3.2, 3.1, 3.6, 3.5, 3.5, 3.2, 3.1,
3.4), col3 = c(1.4, 1.4, 1.3, 1.5, 1.4, 3.4, 3.4, 1.3, 1.5, 3.4
), col4 = c("A", "A", "A", "A", "A", "B", "B", "B", "B", "B"),
count = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), r_new = c(5.6, 5.6,
5.6, 5.6, 5.6, 9.6, 9.6, 9.6, 9.6, 9.6)), .Names = c("col1",
"col2", "col3", "col4", "count", "r_new"), row.names = c(NA,
-10L), class = c("data.table", "data.frame"))
col1 col2 col3 col4 count r_new
1: 5.1 3.5 1.4 A 1 5.6
2: 5.1 3.5 1.4 A 1 5.6
3: 4.7 3.2 1.3 A 1 5.6
4: 4.6 3.1 1.5 A 1 5.6
5: 5.0 3.6 1.4 A 1 5.6
6: 5.1 3.5 3.4 B 1 9.6
7: 5.1 3.5 3.4 B 1 9.6
8: 4.7 3.2 1.3 B 1 9.6
9: 4.6 3.1 1.5 B 1 9.6
10: 5.1 3.4 3.4 B 1 9.6
编辑2:第三名
col1 col2 col3 col4 count r_new
1: 5.1 3.5 1.4 A 1 5.6
2: 5.1 3.5 1.4 A 1 5.6
3: 4.7 3.2 1.3 A 1 5.6
4: 4.6 3.1 1.5 A 1 5.6
5: 5.0 3.6 1.4 A 1 5.6
6: 5.1 3.5 3.4 B 1 6.2
7: 5.1 3.5 3.4 B 1 6.2
8: 4.7 3.2 1.3 B 1 6.2
9: 4.6 3.1 1.5 B 1 6.2
10: 5.1 3.5 3.4 B 1 6.2
structure(list(col1 = c(5.1, 5.1, 4.7, 4.6, 5, 5.1, 5.1, 4.7,
4.6, 5.1), col2 = c(3.5, 3.5, 3.2, 3.1, 3.6, 3.5, 3.5, 3.2, 3.1,
3.5), col3 = c(1.4, 1.4, 1.3, 1.5, 1.4, 3.4, 3.4, 1.3, 1.5, 3.4
), col4 = c("A", "A", "A", "A", "A", "B", "B", "B", "B", "B"),
count = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), r_new = c(5.6, 5.6,
5.6, 5.6, 5.6, 6.2, 6.2, 6.2, 6.2, 6.2)), .Names = c("col1",
"col2", "col3", "col4", "count", "r_new"), row.names = c(NA,
-10L), class = c("data.table", "data.frame"))
最佳答案
我们可以使用col3在j中将?data.table::duplicated子集化。
dat[, r_new := sum(col3[!duplicated(.SD, by = c("col1","col2"))], na.rm = T), by = col4]
> dat
# col1 col2 col3 col4 count r_new
# 1: 5.1 3.5 1.4 A 1 5.6
# 2: 5.1 3.5 1.4 A 1 5.6
# 3: 4.7 3.2 1.3 A 1 5.6
# 4: 4.6 3.1 1.5 A 1 5.6
# 5: 5.0 3.6 1.4 A 1 5.6
# 6: 5.1 3.5 3.4 B 1 6.2
# 7: 5.1 3.5 3.4 B 1 6.2
# 8: 4.7 3.2 1.3 B 1 6.2
# 9: 4.6 3.1 1.5 B 1 6.2
#10: 5.1 3.5 3.4 B 1 6.2
关于r - 在data.table中添加行，但在某些列采用相同值时不添加行，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/36232684/