對行求和並添加到 R 中的下一行
[英]Sum rows and adding to the next row in R
問題描述
我想總結 Col1 中 Col2 等於 0 的行。並將總和添加到 Col1 中的下一個值。 我在下面展示一個例子。 我在數據框中有很多產品。 我從這個開始：
library(dplyr)
TD %>% group_by(Product,Date) %>% mutate(Sum = sum(Col1[Col2 == 0])[1]) %>%
mutate(Expected = Col1)
Date <- seq(as.Date("2021-01-01"), as.Date("2021-01-07"), by = "day")
Product<-rep("A",7)
Col1 <- c(13, 10, 15, 7, 9, 4, 3)
Col2 <- c(7, 0, 0, 8, 0, 0, 27)
Expected <- c(13, 10, 15, 32, 9, 4, 16)
TD <- data.frame(Date, Product, Col1, Col2, Expected)
其他數據：
Date Product Col1 Col2 Expected2
<date> <chr> <dbl> <dbl> <dbl>
1 2021-02-12 831 15 384 631
2 2021-02-13 831 11 373 631
3 2021-02-14 831 13 360 631
4 2021-02-15 831 14 826 631
5 2020-12-03 832 10 11 20
6 2020-12-04 832 10 1 20
7 2020-12-05 832 7 0 7
8 2020-12-06 832 11 0 11
9 2020-12-07 832 13 0 13
10 2020-12-08 832 10 0 10
structure(list(Date = structure(c(18670, 18671, 18672, 18673,
18599, 18600, 18601, 18602, 18603, 18604, 18605, 18606, 18607,
18608, 18609, 18610, 18611, 18612, 18613, 18614, 18615, 18616,
18617, 18618, 18619, 18620, 18621, 18622, 18623, 18624), class = "Date"),
Product = c("831", "831", "831", "831", "832", "832", "832",
"832", "832", "832", "832", "832", "832", "832", "832", "832",
"832", "832", "832", "832", "832", "832", "832", "832", "832",
"832", "832", "832", "832", "832"), Col1 = c(15, 11, 13,
14, 10, 10, 7, 11, 13, 10, 8, 11, 9, 8, 10, 17, 15, 17, 16,
16, 14, 14, 15, 17, 18, 16, 17, 18, 18, 8), Col2 = c(384,
373, 360, 826, 11, 1, 0, 0, 0, 0, 0, 70, 61, 53, 43, 26,
11, 0, 0, 84, 70, 56, 41, 24, 6, 0, 0, 0, 0, 0), Expected2 = c(631,
631, 631, 631, 20, 20, 7, 11, 13, 10, 8, 119, 119, 119, 119,
119, 119, 17, 16, 127, 127, 127, 127, 127, 127, 16, 17, 18,
18, 8)), row.names = c(NA, -30L), class = c("tbl_df", "tbl",
"data.frame"))
1 個解決方案
解決方案1
1 已采納 2020-12-09 23:22:44
我們可以做的
library(dplyr)
TD %>%
group_by(Product) %>%
group_by(grp = cumsum(lag(Col2 != 0, default = FALSE)), .add = TRUE) %>%
mutate(Expected2 = sum(Col1)) %>%
group_by(Product) %>%
mutate(Expected2 = case_when(Col2 == 0 | !any(Col2 == 0) ~
Col1, TRUE ~ Expected2)) %>%
ungroup %>%
select(-grp)
-輸出
# A tibble: 7 x 6
# Date Product Col1 Col2 Expected Expected2
# <date> <chr> <dbl> <dbl> <dbl> <dbl>
#1 2021-01-01 A 13 7 13 13
#2 2021-01-02 A 10 0 10 10
#3 2021-01-03 A 15 0 15 15
#4 2021-01-04 A 7 8 32 32
#5 2021-01-05 A 9 0 9 9
#6 2021-01-06 A 4 0 4 4
#7 2021-01-07 A 3 27 16 16
- 測試第二個數據集
TD2 %>%
group_by(Product) %>%
group_by(grp = cumsum(lag(Col2 != 0, default = FALSE)), .add = TRUE)%>%
mutate(tmp = sum(Col1), Expected2 = case_when(any(Col2 == 0) &
(row_number() == n() & Col2 != 0) ~ tmp, TRUE ~ Col1)) %>%
ungroup %>%
select(-grp, -tmp)
-輸出
# A tibble: 15 x 5
# Date Product Col1 Col2 Expected2
# <chr> <chr> <int> <int> <int>
# 1 2020-12-03 00:00:00 B 10 206 10
# 2 2020-12-04 00:00:00 B 5 364 5
# 3 2020-12-05 00:00:00 B 10 354 10
# 4 2020-12-06 00:00:00 B 8 346 8
# 5 2020-12-07 00:00:00 B 5 341 5
# 6 2020-12-08 00:00:00 B 8 333 8
# 7 2020-12-09 00:00:00 B 12 321 12
# 8 2020-12-10 00:00:00 B 5 316 5
# 9 2020-12-11 00:00:00 B 7 309 7
#10 2020-12-12 00:00:00 B 13 296 13
#11 2020-12-13 00:00:00 B 9 287 9
#12 2020-12-14 00:00:00 B 11 276 11
#13 2020-12-15 00:00:00 B 10 266 10
#14 2020-12-16 00:00:00 B 17 249 17
#15 2020-12-17 00:00:00 B 14 235 14
或者圖像數據
TD3 %>%
group_by(Product) %>%
group_by(grp = cumsum(lag(Col2 != 0, default = FALSE)), .add = TRUE) %>%
mutate(tmp = sum(Col1), Expected2 = case_when(any(Col2 == 0) &
(row_number() == n() & Col2 != 0) ~ tmp, TRUE ~ Col1)) %>%
ungroup %>%
select(-grp, -tmp)
-輸出
# A tibble: 21 x 4
# Product Col1 Col2 Expected2
# <chr> <dbl> <dbl> <dbl>
# 1 C 11 52 11
# 2 C 7 45 7
# 3 C 6 39 6
# 4 C 15 24 15
# 5 C 14 10 14
# 6 C 10 0 10
# 7 C 8 0 8
# 8 C 10 125 28
# 9 C 12 113 12
#10 C 11 102 11
# … with 11 more rows
或使用 OP 的最新dput數據
TD4 %>%
group_by(Product) %>%
group_by(grp = cumsum(lag(Col2 != 0, default = FALSE)), .add = TRUE) %>%
mutate(tmp = sum(Col1), Expected2 = case_when(any(Col2 == 0) &
(row_number() == n() & Col2 != 0) ~ tmp, TRUE ~ Col1)) %>%
ungroup %>%
select(-grp, -tmp) %>%
as.data.frame
-輸出
# Date Product Col1 Col2 Expected2
#1 2021-02-12 831 15 384 15
#2 2021-02-13 831 11 373 11
#3 2021-02-14 831 13 360 13
#4 2021-02-15 831 14 826 14
#5 2020-12-03 832 10 11 10
#6 2020-12-04 832 10 1 10
#7 2020-12-05 832 7 0 7
#8 2020-12-06 832 11 0 11
#9 2020-12-07 832 13 0 13
#10 2020-12-08 832 10 0 10
#11 2020-12-09 832 8 0 8
#12 2020-12-10 832 11 70 60
#13 2020-12-11 832 9 61 9
#14 2020-12-12 832 8 53 8
#15 2020-12-13 832 10 43 10
#16 2020-12-14 832 17 26 17
#17 2020-12-15 832 15 11 15
#18 2020-12-16 832 17 0 17
#19 2020-12-17 832 16 0 16
#20 2020-12-18 832 16 84 49
#21 2020-12-19 832 14 70 14
#22 2020-12-20 832 14 56 14
#23 2020-12-21 832 15 41 15
#24 2020-12-22 832 17 24 17
#25 2020-12-23 832 18 6 18
#26 2020-12-24 832 16 0 16
#27 2020-12-25 832 17 0 17
#28 2020-12-26 832 18 0 18
#29 2020-12-27 832 18 0 18
#30 2020-12-28 832 8 0 8
數據
TD2 <- structure(list(Date = c("2020-12-03 00:00:00", "2020-12-04 00:00:00",
"2020-12-05 00:00:00", "2020-12-06 00:00:00", "2020-12-07 00:00:00",
"2020-12-08 00:00:00", "2020-12-09 00:00:00", "2020-12-10 00:00:00",
"2020-12-11 00:00:00", "2020-12-12 00:00:00", "2020-12-13 00:00:00",
"2020-12-14 00:00:00", "2020-12-15 00:00:00", "2020-12-16 00:00:00",
"2020-12-17 00:00:00"), Product = c("B", "B", "B", "B", "B",
"B", "B", "B", "B", "B", "B", "B", "B", "B", "B"), Col1 = c(10L,
5L, 10L, 8L, 5L, 8L, 12L, 5L, 7L, 13L, 9L, 11L, 10L, 17L, 14L
), Col2 = c(206L, 364L, 354L, 346L, 341L, 333L, 321L, 316L, 309L,
296L, 287L, 276L, 266L, 249L, 235L), Expected2 = c(144L, 144L,
144L, 144L, 144L, 144L, 144L, 144L, 144L, 144L, 144L, 144L, 144L,
144L, 144L)), class = "data.frame", row.names = c("1", "2", "3",
"4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15"
))
TD3 <- structure(list(Product = c("C", "C", "C", "C", "C", "C", "C",
"C", "C", "C", "C", "C", "C", "C", "C", "C", "C", "C", "C", "C",
"C"), Col1 = c(11, 7, 6, 15, 14, 10, 8, 10, 12, 11, 10, 20, 20,
22, 19, 23, 21, 20, 26, 26, 27), Col2 = c(52, 45, 39, 24, 10,
0, 0, 125, 113, 102, 92, 72, 52, 30, 11, 138, 117, 97, 71, 45,
18)), class = "data.frame", row.names = c(NA, -21L))
如何將行除以行總和和矩陣中滿足特定條件（行總和> 100）的行？
[英]How do I divide rows by the row sum and rows that meet a certain condition (row Sum >100)in matrix?r
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