r - 使用分割、剪切和重复函数来过滤R中的数据

Question

我有一个如下所示的数据集。

date <- strptime(c("2011-09-01 00:00:00","2011-09-01 06:00:00","2011-09-01 12:00:00","2011-09-01 18:00:00","2011-09-02 00:00:00",
"2011-09-02 06:00:00","2011-09-02 12:00:00","2011-09-02 18:00:00","2011-09-03 00:00:00","2011-09-03 06:00:00","2011-09-03 12:00:00",
"2011-09-03 18:00:00","2011-09-04 00:00:00","2011-09-04 06:00:00","2011-09-04 12:00:00","2011-09-04 18:00:00","2011-09-05 00:00:00",
"2011-09-05 06:00:00","2011-09-05 12:00:00","2011-09-05 18:00:00","2011-09-06 00:00:00"), format ="%Y-%m-%d %H:%M:%S")

volt <- c(7,8,9,10, 7, 8, 9, 10,  6.1, 11.1,  9.1,  10.1, 7, 8,  9, 10, 6.3, 9.4, 1.3, 19.1, 5.6)

sampV <- data.frame(date,volt)
sampV


               date volt
2011-09-01 00:00:00 7
2011-09-01 06:00:00 8
2011-09-01 12:00:00 9
2011-09-01 18:00:00 10
2011-09-02 00:00:00 7
2011-09-02 06:00:00 8
2011-09-02 12:00:00 9
2011-09-02 18:00:00 10
2011-09-03 00:00:00 6.1
2011-09-03 06:00:00 11.1
2011-09-03 12:00:00 9.1
2011-09-03 18:00:00 10.1
2011-09-04 00:00:00 7
2011-09-04 06:00:00 8
2011-09-04 12:00:00 9
2011-09-04 18:00:00 10
2011-09-05 00:00:00 6.3
2011-09-05 06:00:00 9.4
2011-09-05 12:00:00 1.3
2011-09-05 18:00:00 19.1
2011-09-06 00:00:00 5.6

现在我想使用日期列每天对数据进行分组，然后检查 v 中的结果分组是否重复。例如，9 月 1 日和 2 日的“伏特”数据会重复 (7,8,9,10)。

我一直在尝试使用此代码将其分成不同的日子，但这是我所能做到的。

t1 <- strptime("2011-09-01 00:00:00",format="%Y-%m-%d %H:%M:%S")
t2 <- strptime("2011-09-06 00:00:00",format="%Y-%m-%d %H:%M:%S")

seqD <- seq(t1,t2, by="day")
ctD <- cut(sampV$date, seqD, labels=F )
spD <- split(sampV$date,ctD)

所以我的问题是，如何使用重复函数或任何与此相关的函数提取从一天复制到下一天的数据？我只是 R 的初学者，我仍在学习诀窍，所以我们将非常感谢您的帮助。谢谢

Answer 1

假设我正确理解了您的问题，这是一种仅使用 split 和 duplicate 的方法:

days <- format(sampV$date, '%Y%m%d')
filtered <- split(sampV, days)[! duplicated(split(sampV$volt, days))]
do.call(rbind, filtered)

#                            date volt
# 20110901.1  2011-09-01 00:00:00  7.0
# 20110901.2  2011-09-01 06:00:00  8.0
# 20110901.3  2011-09-01 12:00:00  9.0
# 20110901.4  2011-09-01 18:00:00 10.0
# 20110903.9  2011-09-03 00:00:00  6.1
# 20110903.10 2011-09-03 06:00:00 11.1
# 20110903.11 2011-09-03 12:00:00  9.1
# 20110903.12 2011-09-03 18:00:00 10.1
# 20110905.17 2011-09-05 00:00:00  6.3
# 20110905.18 2011-09-05 06:00:00  9.4
# 20110905.19 2011-09-05 12:00:00  1.3
# 20110905.20 2011-09-05 18:00:00 19.1
# 20110906    2011-09-06 00:00:00  5.6