[英]conditional cumulative sum using dplyr
我的數據框看起來像這樣,我想要兩個單獨的累積列,一個用於基金A,另一個用於基金B.
Name Event SalesAmount Fund Cum-A(desired) Cum-B(desired)
John Webinar NA NA NA NA
John Sale 1000 A 1000 NA
John Sale 2000 B 1000 2000
John Sale 3000 A 4000 2000
John Email NA NA 4000 2000
Tom Webinar NA NA NA NA
Tom Sale 1000 A 1000 NA
Tom Sale 2000 B 1000 2000
Tom Sale 3000 A 4000 2000
Tom Email NA NA 4000 2000
I have tried:
df<-
df %>%
group_by(Name)%>%
mutate(Cum-A = as.numeric(ifelse(Fund=="A",cumsum(SalesAmount),0)))%>%
mutate(Cum-B = as.numeric(ifelse(Fund=="B",cumsum(SalesAmount),0)))
但這完全不是我想要的,因為它向我展示了兩個基金的運行總額,盡管只是在基金匹配的時候。 請幫助。
怎么樣:
library(dplyr)
d %>%
group_by(Name) %>%
mutate(cA=cumsum(ifelse(!is.na(Fund) & Fund=="A",SalesAmount,0))) %>%
mutate(cB=cumsum(ifelse(!is.na(Fund) & Fund=="B",SalesAmount,0)))
輸出:
Source: local data frame [10 x 8]
Groups: Name
Name Event SalesAmount Fund Cum.A.desired. Cum.B.desired. cA cB
1 John Webinar NA NA NA NA 0 0
2 John Sale 1000 A 1000 NA 1000 0
3 John Sale 2000 B 1000 2000 1000 2000
4 John Sale 3000 A 4000 2000 4000 2000
5 John Email NA NA 4000 2000 4000 2000
6 Tom Webinar NA NA NA NA 0 0
7 Tom Sale 1000 A 1000 NA 1000 0
8 Tom Sale 2000 B 1000 2000 1000 2000
9 Tom Sale 3000 A 4000 2000 4000 2000
10 Tom Email NA NA 4000 2000 4000 2000
如果需要,之后可以用NA
替換結果列中的零:
result$cA[result$cA==0] <- NA
result$cB[result$cB==0] <- NA
您的輸入數據集:
d <- structure(list(Name = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L), .Label = c("John", "Tom"), class = "factor"), Event = structure(c(3L, 2L, 2L, 2L, 1L, 3L, 2L, 2L, 2L, 1L), .Label = c("Email", "Sale", "Webinar"), class = "factor"), SalesAmount = c(NA, 1000L, 2000L, 3000L, NA, NA, 1000L, 2000L, 3000L, NA), Fund = structure(c(NA, 1L, 2L, 1L, NA, NA, 1L, 2L, 1L, NA), .Label = c("A", "B"), class = "factor"), Cum.A.desired. = c(NA, 1000L, 1000L, 4000L, 4000L, NA, 1000L, 1000L, 4000L, 4000L), Cum.B.desired. = c(NA, NA, 2000L, 2000L, 2000L, NA, NA, 2000L, 2000L, 2000L)), .Names = c("Name", "Event", "SalesAmount", "Fund", "Cum.A.desired.", "Cum.B.desired." ), class = "data.frame", row.names = c(NA, -10L))
這是一種使用zoo
和data.table
來推廣更多資金的方法:
# prep
require(data.table)
require(zoo)
setDT(d)
d[,Fund:=as.character(Fund)] # because factors are the worst
uf <- unique(d[Event=="Sale"]$Fund) # collect set of funds
首先,在相關觀察子集上分配累計銷售額:
for (f in uf) d[(Event=="Sale"&Fund==f),paste0('c',f):=cumsum(SalesAmount),by=Name]
然后,進行最后一次觀察:
d[,paste0('c',uf):=lapply(.SD,na.locf,na.rm=FALSE),.SDcols=paste0('c',uf),by=Name]
您可以通過將所有內容全部轉換為單個mutate
來縮短@ Marat的答案:
df %>%
group_by(Name) %>%
mutate(
cA = cumsum(ifelse(!is.na(Fund) & Fund == "A", SalesAmount, 0)),
cB = cumsum(ifelse(!is.na(Fund) & Fund == "B", SalesAmount, 0)),
cA = ifelse(cA == 0, NA, cA),
cB = ifelse(cB == 0, NA, cB)
)
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