我有一些传感器数据，每秒有100个数据条目。在最后一列中是毫秒，目前都是10。如何将时间和日期分组的毫秒数按行求和。
testdata <- structure(list(local_date = c("26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017", "26-06-2017"),
local_time = c("13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:23", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24", "13:58:24" ),
ms = c(10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10)),
.Names = c("local_date", "local_time", "ms"), row.names = c(NA, -200L), class = c("data.table", "data.frame"))
前100行都共享相同的时间（13:58:23）和日期（26-06-2017），但是它们都有10毫秒。结果应该只有一个条目，且每秒10毫秒，并且随后的毫秒将添加到先前的毫秒中。
此代码段将按以下顺序创建结果：
testdata$ms = rep(seq(from = 10, to = 1000, by = 10), 2)
但是由于原始数据不是那么干净，所以我必须按日期和时间对数据进行分组，然后以行方式将毫秒相加。
我更喜欢data.table解决方案，但是dplyr也可以正常工作。
答案 0 :(得分：1)
听起来您需要分组的cumsum：
library(dplyr)
testdata$ms2 = rep(seq(from = 10, to = 1000, by = 10), 2)
testdata %>%
group_by(local_date, local_time) %>%
mutate(cumsum_ms = cumsum(ms))
local_date local_time ms ms2 cumsum_ms
<chr> <chr> <dbl> <dbl> <dbl>
1 26-06-2017 13:58:23 10 10 10
2 26-06-2017 13:58:23 10 20 20
3 26-06-2017 13:58:23 10 30 30
4 26-06-2017 13:58:23 10 40 40
5 26-06-2017 13:58:23 10 50 50
答案 1 :(得分：1)
并添加一个data.table版本：
testdata[, ms := cumsum(ms), by = .(local_time, local_date)]