创建条件 interval/group 以捕获数值变量的总和
Create a conditional interval/group to capture the sum of a numeric variable
我需要使用分类变量和条件知道在特定时间段内下了多少雨。与我提供的示例数据框相比，我的真实数据框有 150 多行，“分箱”或日期时间列的可变性要大得多。我正在寻找一个 for 循环或函数，以根据基于列“位置”的特定条件的特定和可变间隔或时间段来获取降水量的总和（例如“TotalRain”）。此“位置”列有空行、“开始”行或“结束”行。我的想法是在“组”列中创建 intervals/groups 以更好地识别这些 intervals/groups，然后使用这些组或另一个 for 循环求和，然后将该间隔期间的降水总和粘贴到列中“群雨。”
这是一个示例数据集，用于填写提供的“Groups”和“GroupRain”列：
dat<-data.frame(binned=as.POSIXct(c("2020-08-01 06:26:00", "2020-08-01 19:26:00", "2020-08-02 06:26:00", "2020-08-02 19:26:00", "2020-08-03 06:26:00","2020-08-03 19:26:00", "2020-08-04 06:26:00", "2020-08-04 19:26:00", "2020-08-05 06:26:00", "2020-08-05 19:26:00", "2020-08-06 06:26:00", "2020-08-06 19:26:00", "2020-08-07 06:26:00", "2020-08-07 19:26:00", "2020-08-08 06:26:00", "2020-08-08 19:26:00", "2020-08-09 06:26:00", "2020-08-09 19:26:00", "2020-08-10 06:26:00"), tz="America/Chicago"), position=c("","", "", "", "", "Start", "", "", "", "End", "", "", "", "Start", "End", "", "" ,"", "" ), TotalRain= as.numeric(c("0.0", "0.0", "0.1", "0.0", "0.0", "0.0", "0.2", "0.3", "0.0", "0.1", "0.0", "0.3", "0.0", "0.1", "0.0", "0.0", "0.4", "0.0", "0.0")), Groups=as.character(""), GroupRain=as.numeric(""))
这是上面代码中提供的数据帧的图像：
我遇到的问题是创建一个 for 循环或函数，该循环或函数开始对“TotalRain”行求和，直到条件发生或条件正在发生时。例如，我的数据框的前 5 行将是我的第一个 interval/group，我希望“Total Rain”的总和在“position”列等于“Start”时停止求和，然后将这个总数粘贴到第一个间隔结束的“GroupRain”列（例如第 5 行）。此数据框中的第一个“开始”将是我的第二个 interval/group 的开始，它也是 5 行长。对于这一秒 interval/group，我想再次获取“Total Rain”的总和，但是当“position”等于“End”时停止并将总和粘贴到这一行中。第三个间隔从位置不再等于“结束”且为空白（例如第 11 行到第 13 行）开始，一直持续到位置再次等于“开始”（例如第 14 行），并将其总和粘贴到第 13 行。第 4 个interval/group 长 2 行，即第 14 行和第 15 行，并将其总和粘贴到第 15 行。第 5 个也是最后一个 interval/group 长 4 行，即第 16 到 19 行，并且将有它的总和粘贴在第 19 行。下面是一个输出数据框的示例，其中我使用字母表手动创建了 5 interval/groups 并手动求和并将每个间隔的“总雨量”粘贴到“GroupRain”列中。我可以使用 R 中的“LETTERS”包来提供我的 interval/group 名称（A、B、C 等）。下面提供了我想要最终得到的数据框：
dat2<-data.frame(binned=as.POSIXct(c("2020-08-01 06:26:00", "2020-08-01 19:26:00", "2020-08-02 06:26:00", "2020-08-02 19:26:00", "2020-08-03 06:26:00","2020-08-03 19:26:00", "2020-08-04 06:26:00", "2020-08-04 19:26:00", "2020-08-05 06:26:00", "2020-08-05 19:26:00", "2020-08-06 06:26:00", "2020-08-06 19:26:00", "2020-08-07 06:26:00", "2020-08-07 19:26:00", "2020-08-08 06:26:00", "2020-08-08 19:26:00", "2020-08-09 06:26:00", "2020-08-09 19:26:00", "2020-08-10 06:26:00"), tz="America/Chicago"), position=c("","", "", "", "", "Start", "", "", "", "End", "", "", "", "Start", "End", "", "" ,"", "" ), TotalRain= as.numeric(c("0.0", "0.0", "0.1", "0.0", "0.0", "0.0", "0.2", "0.3", "0.0", "0.1", "0.0", "0.3", "0.0", "0.1", "0.0", "0.0", "0.4", "0.0", "0.0")), Groups=c("A", "A", "A", "A", "A", "B", "B", "B", "B", "B", "C", "C", "C", "D", "D", "E", "E", "E", "E"), GroupRain=as.numeric(c("", "", "", "", "0.1", "", "", "", "", "0.6", "0.0", "", "0.3", "", "0.1", "", "", "", "0.4")))
A 组或我的第一个间隔总共有 0.1 英寸。 B 组或我的第二个间隔总共有 0.6 英寸。 C 组总共有 0.3 英寸。 D 组总共有 0.1 英寸。而E组一共0.4寸。
我的最终目标是能够在不丢失我需要保留的所有中间数字数据（如雨）的情况下过滤数据帧。当我根据“开始”和“结束”位置进行过滤时，我希望在该间隔内已经将汇总的“TotalRain”列显示为“GroupRain”。
例如，我的最终代码将是这样的，它会生成以下图像并向我显示 interval/group B 总共下了 0.6 英寸的雨。 Interval/group D 总共下了 0.1 英寸的雨。
dat3<- dat2 %>%filter(position == "Start"|position == "End")
基础 R
dat$ends <- rev(cumsum(rev(dat$position == "End")))
dat$withstarts <- with(dat, ave(position, ends, FUN = function(z) cumsum(z == "Start")))
dat$GroupRain <- with(dat, ave(TotalRain, list(ends, withstarts), FUN = function(z) c(rep(NA, length(z)-1), sum(z)), drop=TRUE))
with(dat, ave(position, list(ends, withstarts), FUN = function(z) !all(c("Start","End") %in% z)))
# [1] "TRUE" "TRUE" "TRUE" "TRUE" "TRUE" "FALSE" "FALSE" "FALSE" "FALSE" "FALSE" "TRUE"
# [12] "TRUE" "TRUE" "FALSE" "FALSE" "TRUE" "TRUE" "TRUE" "TRUE"
dat$GroupRain[with(dat, ave(position, list(ends, withstarts), FUN = function(z) !all(c("Start","End") %in% z))) == "TRUE"] <- NA
dat[c("ends","withstarts")] <- NULL
dat
# binned position TotalRain Groups GroupRain
# 1 2020-08-01 06:26:00 0.0 NA
# 2 2020-08-01 19:26:00 0.0 NA
# 3 2020-08-02 06:26:00 0.1 NA
# 4 2020-08-02 19:26:00 0.0 NA
# 5 2020-08-03 06:26:00 0.0 NA
# 6 2020-08-03 19:26:00 Start 0.0 NA
# 7 2020-08-04 06:26:00 0.2 NA
# 8 2020-08-04 19:26:00 0.3 NA
# 9 2020-08-05 06:26:00 0.0 NA
# 10 2020-08-05 19:26:00 End 0.1 0.6
# 11 2020-08-06 06:26:00 0.0 NA
# 12 2020-08-06 19:26:00 0.3 NA
# 13 2020-08-07 06:26:00 0.0 NA
# 14 2020-08-07 19:26:00 Start 0.1 NA
# 15 2020-08-08 06:26:00 End 0.0 0.1
# 16 2020-08-08 19:26:00 0.0 NA
# 17 2020-08-09 06:26:00 0.4 NA
# 18 2020-08-09 19:26:00 0.0 NA
# 19 2020-08-10 06:26:00 0.0 NA
或者，在添加 ends 和 withstarts 之后（以上）：
res <- aggregate(TotalRain ~ ends + withstarts, data = dat, FUN = sum)
names(res)[3] <- "GroupRain"
dat2 <- merge(dat, res, by = c("ends", "withstarts"))
dat2$GroupRain[dat2$position != "End"] <- NA
dat2[,c("ends","withstarts")] <- NULL
dat2
# binned position TotalRain Groups GroupRain
# 1 2020-08-08 19:26:00 0.0 NA
# 2 2020-08-09 06:26:00 0.4 NA
# 3 2020-08-09 19:26:00 0.0 NA
# 4 2020-08-10 06:26:00 0.0 NA
# 5 2020-08-06 06:26:00 0.0 NA
# 6 2020-08-06 19:26:00 0.3 NA
# 7 2020-08-07 06:26:00 0.0 NA
# 8 2020-08-07 19:26:00 Start 0.1 NA
# 9 2020-08-08 06:26:00 End 0.0 0.1
# 10 2020-08-01 06:26:00 0.0 NA
# 11 2020-08-01 19:26:00 0.0 NA
# 12 2020-08-02 06:26:00 0.1 NA
# 13 2020-08-02 19:26:00 0.0 NA
# 14 2020-08-03 06:26:00 0.0 NA
# 15 2020-08-03 19:26:00 Start 0.0 NA
# 16 2020-08-04 06:26:00 0.2 NA
# 17 2020-08-04 19:26:00 0.3 NA
# 18 2020-08-05 06:26:00 0.0 NA
# 19 2020-08-05 19:26:00 End 0.1 0.6
dplyr
library(dplyr)
dat %>%
group_by(ends = rev(cumsum(rev(position == "End")))) %>%
group_by(withstarts = cumsum(position == "Start"), add = TRUE) %>%
mutate(GroupRain = if_else(all(c("Start", "End") %in% position) & row_number() == n(), sum(TotalRain), NA_real_)) %>%
ungroup() %>%
select(-ends, -withstarts)
# # A tibble: 19 x 5
# binned position TotalRain Groups GroupRain
# <dttm> <chr> <dbl> <chr> <dbl>
# 1 2020-08-01 06:26:00 "" 0 "" NA
# 2 2020-08-01 19:26:00 "" 0 "" NA
# 3 2020-08-02 06:26:00 "" 0.1 "" NA
# 4 2020-08-02 19:26:00 "" 0 "" NA
# 5 2020-08-03 06:26:00 "" 0 "" NA
# 6 2020-08-03 19:26:00 "Start" 0 "" NA
# 7 2020-08-04 06:26:00 "" 0.2 "" NA
# 8 2020-08-04 19:26:00 "" 0.3 "" NA
# 9 2020-08-05 06:26:00 "" 0 "" NA
# 10 2020-08-05 19:26:00 "End" 0.1 "" 0.6
# 11 2020-08-06 06:26:00 "" 0 "" NA
# 12 2020-08-06 19:26:00 "" 0.3 "" NA
# 13 2020-08-07 06:26:00 "" 0 "" NA
# 14 2020-08-07 19:26:00 "Start" 0.1 "" NA
# 15 2020-08-08 06:26:00 "End" 0 "" 0.1
# 16 2020-08-08 19:26:00 "" 0 "" NA
# 17 2020-08-09 06:26:00 "" 0.4 "" NA
# 18 2020-08-09 19:26:00 "" 0 "" NA
# 19 2020-08-10 06:26:00 "" 0 "" NA
数据
dat <- structure(list(binned = structure(c(1596281160, 1596327960, 1596367560, 1596414360, 1596453960, 1596500760, 1596540360, 1596587160, 1596626760, 1596673560, 1596713160, 1596759960, 1596799560, 1596846360, 1596885960, 1596932760, 1596972360, 1597019160, 1597058760), class = c("POSIXct", "POSIXt"), tzone = "America/Chicago"), position = c("", "", "", "", "", "Start", "", "", "", "End", "", "", "", "Start", "End", "", "", "", ""), TotalRain = c(0, 0, 0.1, 0, 0, 0, 0.2, 0.3, 0, 0.1, 0, 0.3, 0, 0.1, 0, 0, 0.4, 0, 0), Groups = c("", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""), GroupRain = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_)), row.names = c(NA, -19L), class = "data.frame")
我需要使用分类变量和条件知道在特定时间段内下了多少雨。与我提供的示例数据框相比，我的真实数据框有 150 多行，“分箱”或日期时间列的可变性要大得多。我正在寻找一个 for 循环或函数，以根据基于列“位置”的特定条件的特定和可变间隔或时间段来获取降水量的总和（例如“TotalRain”）。此“位置”列有空行、“开始”行或“结束”行。我的想法是在“组”列中创建 intervals/groups 以更好地识别这些 intervals/groups，然后使用这些组或另一个 for 循环求和，然后将该间隔期间的降水总和粘贴到列中“群雨。”
这是一个示例数据集，用于填写提供的“Groups”和“GroupRain”列：
dat<-data.frame(binned=as.POSIXct(c("2020-08-01 06:26:00", "2020-08-01 19:26:00", "2020-08-02 06:26:00", "2020-08-02 19:26:00", "2020-08-03 06:26:00","2020-08-03 19:26:00", "2020-08-04 06:26:00", "2020-08-04 19:26:00", "2020-08-05 06:26:00", "2020-08-05 19:26:00", "2020-08-06 06:26:00", "2020-08-06 19:26:00", "2020-08-07 06:26:00", "2020-08-07 19:26:00", "2020-08-08 06:26:00", "2020-08-08 19:26:00", "2020-08-09 06:26:00", "2020-08-09 19:26:00", "2020-08-10 06:26:00"), tz="America/Chicago"), position=c("","", "", "", "", "Start", "", "", "", "End", "", "", "", "Start", "End", "", "" ,"", "" ), TotalRain= as.numeric(c("0.0", "0.0", "0.1", "0.0", "0.0", "0.0", "0.2", "0.3", "0.0", "0.1", "0.0", "0.3", "0.0", "0.1", "0.0", "0.0", "0.4", "0.0", "0.0")), Groups=as.character(""), GroupRain=as.numeric(""))
这是上面代码中提供的数据帧的图像：
我遇到的问题是创建一个 for 循环或函数，该循环或函数开始对“TotalRain”行求和，直到条件发生或条件正在发生时。例如，我的数据框的前 5 行将是我的第一个 interval/group，我希望“Total Rain”的总和在“position”列等于“Start”时停止求和，然后将这个总数粘贴到第一个间隔结束的“GroupRain”列（例如第 5 行）。此数据框中的第一个“开始”将是我的第二个 interval/group 的开始，它也是 5 行长。对于这一秒 interval/group，我想再次获取“Total Rain”的总和，但是当“position”等于“End”时停止并将总和粘贴到这一行中。第三个间隔从位置不再等于“结束”且为空白（例如第 11 行到第 13 行）开始，一直持续到位置再次等于“开始”（例如第 14 行），并将其总和粘贴到第 13 行。第 4 个interval/group 长 2 行，即第 14 行和第 15 行，并将其总和粘贴到第 15 行。第 5 个也是最后一个 interval/group 长 4 行，即第 16 到 19 行，并且将有它的总和粘贴在第 19 行。下面是一个输出数据框的示例，其中我使用字母表手动创建了 5 interval/groups 并手动求和并将每个间隔的“总雨量”粘贴到“GroupRain”列中。我可以使用 R 中的“LETTERS”包来提供我的 interval/group 名称（A、B、C 等）。下面提供了我想要最终得到的数据框：
dat2<-data.frame(binned=as.POSIXct(c("2020-08-01 06:26:00", "2020-08-01 19:26:00", "2020-08-02 06:26:00", "2020-08-02 19:26:00", "2020-08-03 06:26:00","2020-08-03 19:26:00", "2020-08-04 06:26:00", "2020-08-04 19:26:00", "2020-08-05 06:26:00", "2020-08-05 19:26:00", "2020-08-06 06:26:00", "2020-08-06 19:26:00", "2020-08-07 06:26:00", "2020-08-07 19:26:00", "2020-08-08 06:26:00", "2020-08-08 19:26:00", "2020-08-09 06:26:00", "2020-08-09 19:26:00", "2020-08-10 06:26:00"), tz="America/Chicago"), position=c("","", "", "", "", "Start", "", "", "", "End", "", "", "", "Start", "End", "", "" ,"", "" ), TotalRain= as.numeric(c("0.0", "0.0", "0.1", "0.0", "0.0", "0.0", "0.2", "0.3", "0.0", "0.1", "0.0", "0.3", "0.0", "0.1", "0.0", "0.0", "0.4", "0.0", "0.0")), Groups=c("A", "A", "A", "A", "A", "B", "B", "B", "B", "B", "C", "C", "C", "D", "D", "E", "E", "E", "E"), GroupRain=as.numeric(c("", "", "", "", "0.1", "", "", "", "", "0.6", "0.0", "", "0.3", "", "0.1", "", "", "", "0.4")))
A 组或我的第一个间隔总共有 0.1 英寸。 B 组或我的第二个间隔总共有 0.6 英寸。 C 组总共有 0.3 英寸。 D 组总共有 0.1 英寸。而E组一共0.4寸。
我的最终目标是能够在不丢失我需要保留的所有中间数字数据（如雨）的情况下过滤数据帧。当我根据“开始”和“结束”位置进行过滤时，我希望在该间隔内已经将汇总的“TotalRain”列显示为“GroupRain”。 例如，我的最终代码将是这样的，它会生成以下图像并向我显示 interval/group B 总共下了 0.6 英寸的雨。 Interval/group D 总共下了 0.1 英寸的雨。
dat3<- dat2 %>%filter(position == "Start"|position == "End")
基础 R
dat$ends <- rev(cumsum(rev(dat$position == "End")))
dat$withstarts <- with(dat, ave(position, ends, FUN = function(z) cumsum(z == "Start")))
dat$GroupRain <- with(dat, ave(TotalRain, list(ends, withstarts), FUN = function(z) c(rep(NA, length(z)-1), sum(z)), drop=TRUE))
with(dat, ave(position, list(ends, withstarts), FUN = function(z) !all(c("Start","End") %in% z)))
# [1] "TRUE" "TRUE" "TRUE" "TRUE" "TRUE" "FALSE" "FALSE" "FALSE" "FALSE" "FALSE" "TRUE"
# [12] "TRUE" "TRUE" "FALSE" "FALSE" "TRUE" "TRUE" "TRUE" "TRUE"
dat$GroupRain[with(dat, ave(position, list(ends, withstarts), FUN = function(z) !all(c("Start","End") %in% z))) == "TRUE"] <- NA
dat[c("ends","withstarts")] <- NULL
dat
# binned position TotalRain Groups GroupRain
# 1 2020-08-01 06:26:00 0.0 NA
# 2 2020-08-01 19:26:00 0.0 NA
# 3 2020-08-02 06:26:00 0.1 NA
# 4 2020-08-02 19:26:00 0.0 NA
# 5 2020-08-03 06:26:00 0.0 NA
# 6 2020-08-03 19:26:00 Start 0.0 NA
# 7 2020-08-04 06:26:00 0.2 NA
# 8 2020-08-04 19:26:00 0.3 NA
# 9 2020-08-05 06:26:00 0.0 NA
# 10 2020-08-05 19:26:00 End 0.1 0.6
# 11 2020-08-06 06:26:00 0.0 NA
# 12 2020-08-06 19:26:00 0.3 NA
# 13 2020-08-07 06:26:00 0.0 NA
# 14 2020-08-07 19:26:00 Start 0.1 NA
# 15 2020-08-08 06:26:00 End 0.0 0.1
# 16 2020-08-08 19:26:00 0.0 NA
# 17 2020-08-09 06:26:00 0.4 NA
# 18 2020-08-09 19:26:00 0.0 NA
# 19 2020-08-10 06:26:00 0.0 NA
或者，在添加 ends 和 withstarts 之后（以上）：
res <- aggregate(TotalRain ~ ends + withstarts, data = dat, FUN = sum)
names(res)[3] <- "GroupRain"
dat2 <- merge(dat, res, by = c("ends", "withstarts"))
dat2$GroupRain[dat2$position != "End"] <- NA
dat2[,c("ends","withstarts")] <- NULL
dat2
# binned position TotalRain Groups GroupRain
# 1 2020-08-08 19:26:00 0.0 NA
# 2 2020-08-09 06:26:00 0.4 NA
# 3 2020-08-09 19:26:00 0.0 NA
# 4 2020-08-10 06:26:00 0.0 NA
# 5 2020-08-06 06:26:00 0.0 NA
# 6 2020-08-06 19:26:00 0.3 NA
# 7 2020-08-07 06:26:00 0.0 NA
# 8 2020-08-07 19:26:00 Start 0.1 NA
# 9 2020-08-08 06:26:00 End 0.0 0.1
# 10 2020-08-01 06:26:00 0.0 NA
# 11 2020-08-01 19:26:00 0.0 NA
# 12 2020-08-02 06:26:00 0.1 NA
# 13 2020-08-02 19:26:00 0.0 NA
# 14 2020-08-03 06:26:00 0.0 NA
# 15 2020-08-03 19:26:00 Start 0.0 NA
# 16 2020-08-04 06:26:00 0.2 NA
# 17 2020-08-04 19:26:00 0.3 NA
# 18 2020-08-05 06:26:00 0.0 NA
# 19 2020-08-05 19:26:00 End 0.1 0.6
dplyr
library(dplyr)
dat %>%
group_by(ends = rev(cumsum(rev(position == "End")))) %>%
group_by(withstarts = cumsum(position == "Start"), add = TRUE) %>%
mutate(GroupRain = if_else(all(c("Start", "End") %in% position) & row_number() == n(), sum(TotalRain), NA_real_)) %>%
ungroup() %>%
select(-ends, -withstarts)
# # A tibble: 19 x 5
# binned position TotalRain Groups GroupRain
# <dttm> <chr> <dbl> <chr> <dbl>
# 1 2020-08-01 06:26:00 "" 0 "" NA
# 2 2020-08-01 19:26:00 "" 0 "" NA
# 3 2020-08-02 06:26:00 "" 0.1 "" NA
# 4 2020-08-02 19:26:00 "" 0 "" NA
# 5 2020-08-03 06:26:00 "" 0 "" NA
# 6 2020-08-03 19:26:00 "Start" 0 "" NA
# 7 2020-08-04 06:26:00 "" 0.2 "" NA
# 8 2020-08-04 19:26:00 "" 0.3 "" NA
# 9 2020-08-05 06:26:00 "" 0 "" NA
# 10 2020-08-05 19:26:00 "End" 0.1 "" 0.6
# 11 2020-08-06 06:26:00 "" 0 "" NA
# 12 2020-08-06 19:26:00 "" 0.3 "" NA
# 13 2020-08-07 06:26:00 "" 0 "" NA
# 14 2020-08-07 19:26:00 "Start" 0.1 "" NA
# 15 2020-08-08 06:26:00 "End" 0 "" 0.1
# 16 2020-08-08 19:26:00 "" 0 "" NA
# 17 2020-08-09 06:26:00 "" 0.4 "" NA
# 18 2020-08-09 19:26:00 "" 0 "" NA
# 19 2020-08-10 06:26:00 "" 0 "" NA
数据
dat <- structure(list(binned = structure(c(1596281160, 1596327960, 1596367560, 1596414360, 1596453960, 1596500760, 1596540360, 1596587160, 1596626760, 1596673560, 1596713160, 1596759960, 1596799560, 1596846360, 1596885960, 1596932760, 1596972360, 1597019160, 1597058760), class = c("POSIXct", "POSIXt"), tzone = "America/Chicago"), position = c("", "", "", "", "", "Start", "", "", "", "End", "", "", "", "Start", "End", "", "", "", ""), TotalRain = c(0, 0, 0.1, 0, 0, 0, 0.2, 0.3, 0, 0.1, 0, 0.3, 0, 0.1, 0, 0, 0.4, 0, 0), Groups = c("", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""), GroupRain = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_)), row.names = c(NA, -19L), class = "data.frame")