根据其他列的条件提取数据帧行的子集

Question

我有一个dataframe，如下所示：

x <- data.table(Tickers=c("A","A","A","B","B","B","B","D","D","D","D"),
                Type=c("put","call","put","call","call","put","call","put","call","put","call"),
                Strike=c(35,37.5,37.5,10,11,11,12,40,40,42,42),
                Other=sample(20,11))

    Tickers Type Strike Other
 1:       A  put   35.0     6
 2:       A call   37.5     5
 3:       A  put   37.5    13
 4:       B call   10.0    15
 5:       B call   11.0    12
 6:       B  put   11.0     4
 7:       B call   12.0    20
 8:       D  put   40.0     7
 9:       D call   40.0    11
10:       D  put   42.0    10
11:       D call   42.0     1

我正在尝试分析数据的一个子集。我想采用的子集是ticker 和strike 相同的数据。但是我也只想在type 下同时存在put 和call 时获取这些数据。以上面的数据为例，我想返回以下结果：

x[c(2,3,5,6,8:11),]

   Tickers Type Strike Other
1:       A call   37.5     5
2:       A  put   37.5    13
3:       B call   11.0    12
4:       B  put   11.0     4
5:       D  put   40.0     7
6:       D call   40.0    11
7:       D  put   42.0    10
8:       D call   42.0     1

我不确定执行此操作的最佳方法是什么。我的想法是我应该创建另一个列向量，例如

x$id <- paste(x$Tickers,x$Strike,sep="_")

然后使用这个向量只提取有多个 id 的值。

x[x$id %in% x$id[duplicated(x$id)],]

   Tickers Type Strike Other     id
1:       A call   37.5     5 A_37.5
2:       A  put   37.5    13 A_37.5
3:       B call   11.0    12   B_11
4:       B  put   11.0     4   B_11
5:       D  put   40.0     7   D_40
6:       D call   40.0    11   D_40
7:       D  put   42.0    10   D_42
8:       D call   42.0     1   D_42

我不确定这样做的效率如何，因为我的实际数据包含更多行。 此外，此解决方案不会检查 type 的条件，即有一个 put 和一个 call。

标题的措辞可能会好很多，我很抱歉

编辑::: 已查看此帖子Finding ALL duplicate rows, including "elements with smaller subscripts"

我也可以使用这个解决方案：

x$id <- paste(x$Tickers,x$Strike,sep="_")
x[duplicated(x$id) | duplicated(x$id,fromLast=T),]

Answer 1

你可以试试这样的：

x[, select := (.N >= 2 & all(c("put", "call") %in% unique(Type))), by = .(Tickers, Strike)][which(select)]

#   Tickers Type Strike Other select
#1:       A call   37.5    17   TRUE
#2:       A  put   37.5    16   TRUE
#3:       B call   11.0    11   TRUE
#4:       B  put   11.0    20   TRUE
#5:       D  put   40.0     1   TRUE
#6:       D call   40.0    12   TRUE
#7:       D  put   42.0     6   TRUE
#8:       D call   42.0     2   TRUE

另一个想法可能是合并：

x[x, on = .(Tickers, Strike), select := (length(Type) >= 2 & all(c("put", "call") %in% Type)),by = .EACHI][which(select)]

我不完全确定如何绕过分组操作，因为您想确保每个组都有“call”和“put”。我正在考虑使用键，但无法合并“调用”/“放置”方面。

Answer 2

对您的数据进行编辑以给出put 和call 都不存在的情况（我将最后一个“调用”更改为“放置”）：

x <- data.table(Tickers=c("A","A","A","B","B","B","B","D","D","D","D"),
            Type=c("put","call","put","call","call","put","call","put","call","put","put"),
            Strike=c(35,37.5,37.5,10,11,11,12,40,40,42,42),
            Other=sample(20,11))

由于您使用的是data.table，因此您可以使用内置计数器.N 和by 变量来计算组和子集。如果通过计算Type，您可以可靠地确定同时存在put 和call，这可能会起作用：

x[, `:=`(n = .N, types = uniqueN(Type)), by = c('Tickers', 'Strike')][n > 1 & types == 2]

第一组[] 中的部分进行计数，然后[n > 1 & types == 2] 进行子集。

Answer 3

我不是包 data.table 的用户，所以此代码仅是基本 R。

agg <- aggregate(Type ~ Tickers + Strike, data = x, length)
result <- merge(x, subset(agg, Type > 1)[1:2], by = c("Tickers", "Strike"))[, c(1, 3, 2, 4)]
result
#   Tickers Type Strike Other
#1:       A call   37.5    17
#2:       A  put   37.5     7
#3:       B call   11.0    14
#4:       B  put   11.0    20
#5:       D  put   40.0    15
#6:       D call   40.0     2
#7:       D  put   42.0     8
#8:       D call   42.0     1


rm(agg)    # final clean up