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我想向数据表 1 添加列，这些列是对数据表 2 的操作，通过变量连接，并且数据表 2 中的日期是 <= 数据表 1 中的日期。我正在寻找一种解决方案t 计算成本太高（我有大约 20k 行）。

数据表 1 - 我有一个提案、他们的所有者和他们的编辑日期的数据集：

proposal_df <- structure(list(proposal = c(41, 62, 169, 72), owner = c("Adam", 
"Adam", "Alan", "Alan"), totalAtEdit = c(-27, 1000, 151, 1137
), editDate = structure(c(1556014200, 1560762240, 1563966600, 
1540832280), class = c("POSIXct", "POSIXt"), tzone = "UTC")), class = "data.table", row.names = c(NA, 
-4L))

  proposal owner totalAtEdit            editDate
1       41  Adam         -27 2019-04-23 10:10:00
2       62  Adam        1000 2019-06-17 09:04:00
3      169  Alan         151 2019-07-24 11:10:00
4       72  Alan        1137 2018-10-29 16:58:00

数据表 2 - 我有一份提案日志以及它们的获胜或失败日期（outcome == 1或0）：

proposal_log <- structure(list(proposal = c(9, 48, 43, 39, 45, 73, 111, 179, 
115, 146), outcome = c(0, 1, 1, 1, 0, 0, 0, 0, 0, 0), owner = c("Adam", 
"Adam", "Adam", "Adam", "Adam", "Alan", "Alan", "Alan", "Alan", 
"Alan"), totalAtEdit = c(2, 2, 4, 566, 100, 1264, 5000, 75, 493, 
18), editDate = structure(c(1557487860, 1561368780, 1561393140, 
1546446240, 1549463520, 1546614180, 1547196960, 1579603560, 1566925200, 
1536751800), class = c("POSIXct", "POSIXt"), tzone = "UTC")), class = "data.table", row.names = 
c(NA, 
-10L))

   proposal outcome owner totalAtEdit            editDate
1         9       0  Adam           2 2019-05-10 11:31:00
2        48       1  Adam           2 2019-06-24 09:33:00
3        43       1  Adam           4 2019-06-24 16:19:00
4        39       1  Adam         566 2019-01-02 16:24:00
5        45       0  Adam         100 2019-02-06 14:32:00
6        73       0  Alan        1264 2019-01-04 15:03:00
7       111       0  Alan        5000 2019-01-11 08:56:00
8       179       0  Alan          75 2020-01-21 10:46:00
9       115       0  Alan         493 2019-08-27 17:00:00
10      146       0  Alan          18 2018-09-12 11:30:00

我想添加几列，这些列proposal_df是对proposal_log、 加入owner和 where的操作proposal_log$editDate <= proposal_df$editDate：

  • countWon- 提案数量outcome == 1
  • countLost- 提案数量outcome == 0
  • wonValueMean-totalAtEdit提案的平均值，其中outcome == 1
  • pctWon- 提案的百分比outcome == 1

输出如下所示：

  proposal owner totalAtEdit            editDate countWon countLost wonValueMean    pctWon
1       41  Adam         -27 2019-04-23 10:10:00        1         1          566 0.5000000
2       62  Adam        1000 2019-06-17 09:04:00        1         2          566 0.3333333
3      169  Alan         151 2019-07-24 11:10:00        0         3          NaN 0.0000000
4       72  Alan        1137 2018-10-29 16:58:00        0         1          NaN 0.0000000

谢谢！

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2 回答 2

2

可能有一个更优雅的解决方案，但这会在 4 个步骤中提供所需的输出。

首先，将表设置为数据表以执行非等连接。

library(data.table)

setDT(proposal_df)
setDT(proposal_log)

第 1 步：同一所有者和 proposal_log$editDate <= proposal_df$editDate 的非 equi 加入。

Proposals <- proposal_log[proposal_df, on = .(owner, editDate <= editDate)]

这将返回 proposal_log 中满足条件的提案。较小表中的proposal和totalAtEdit变量被添加到结果中，前缀为i..

   proposal outcome owner totalAtEdit            editDate i.proposal i.totalAtEdit
1:       39       1  Adam         566 2019-04-23 10:10:00         41           -27
2:       45       0  Adam         100 2019-04-23 10:10:00         41           -27
3:        9       0  Adam           2 2019-06-17 09:04:00         62          1000
4:       39       1  Adam         566 2019-06-17 09:04:00         62          1000
5:       45       0  Adam         100 2019-06-17 09:04:00         62          1000
6:       73       0  Alan        1264 2019-07-24 11:10:00        169           151
7:      111       0  Alan        5000 2019-07-24 11:10:00        169           151
8:      146       0  Alan          18 2019-07-24 11:10:00        169           151
9:      146       0  Alan          18 2018-10-29 16:58:00         72          1137

第 2 步：将其重新整形为宽格式以计算 ( fun=length) 每个结果的数量i.proposal，然后计算获胜结果的比例（结果 = 1）。

Outcomes <- dcast(Proposals, i.proposal ~ outcome, fun=length)[
  , pctWon := `1`/(`0`+`1`)]

第 3 步totalAtEdit：计算每个提案赢得的结果 ( )的平均值，outcome==1并与提案 ID 上的结果进行内部连接。

Means <- Proposals[outcome==1, .(m_total = mean(totalAtEdit)), by=i.proposal]
Outcomes[Means, on=.(i.proposal), wonValueMean := m_total]

第 4 步：将其与 proposal_df 表连接。

proposal_df[Outcomes, on=c(proposal = "i.proposal")]

   proposal owner totalAtEdit            editDate 0 1    pctWon wonValueMean
1:       41  Adam         -27 2019-04-23 10:10:00 1 1 0.5000000          566
2:       62  Adam        1000 2019-06-17 09:04:00 2 1 0.3333333          566
3:       72  Alan        1137 2018-10-29 16:58:00 1 0 0.0000000           NA
4:      169  Alan         151 2019-07-24 11:10:00 3 0 0.0000000           NA
于 2020-03-22T05:47:40.913 回答
1

另一种选择是使用by=.EACHI：

library(data.table)
setDT(proposal_df)
setDT(proposal_log)
proposal_df[, c("countWon","countLost","wonValueMean","pctWon") := 
    proposal_log[.SD, on=.(owner, editDate<=editDate), by=.EACHI, {
        cw <- sum(outcome==1L)
        .(cw, sum(outcome==0L), mean(x.totalAtEdit[outcome==1L]), cw/.N)
    }][, (1L:2L) := NULL]
]
于 2020-03-23T01:10:31.010 回答