我正在尝试使用两个条件在data.frame或data.table中创建列。我所看到的以及我在下面尝试修改的帖子的不同之处在于我没有条件的“值”，但条件取决于data.frame中的其他变量。
我们假设这是我的数据框：
mydf <- data.frame (Year = c(2000, 2001, 2002, 2004, 2005,
2007, 2000, 2001, 2002, 2003,
2003, 2004, 2005, 2006, 2006, 2007),
Name = c("Tom", "Tom", "Tom", "Fred", "Gill",
"Fred", "Gill", "Gill", "Tom", "Tom",
"Fred", "Fred", "Gill", "Fred", "Gill", "Gill"))
我想了解这3名受试者在过去5年中经历过多少次活动。但是，如果活动日期超过5年，我不想包含它。我想我可以做一个指标变量的总和（如果主题经历了一年中的事件，则设置为1），同时指定Year < Year & Year >= Year-5行的内容。因此，基本上总结了年度小于焦点年份且大于或等于焦点年份前5年的经验。
我已经创建了一个求和指标和焦点年份的变量 - 5
mydf$Ind <- 1
mydf$Yearm5 <- mydf$Year-5
然后我转换为数据表的速度（原始df有+ 60k obs）
library(data.table)
mydf <- data.table(mydf)
现在的问题是我不能让这两个条件起作用。我所看到的帖子似乎都知道一个特定的值来通过子集（例如R data.table subsetting on multiple conditions.），但在我的情况下，值从观察变为观察（不确定这是否意味着我需要做一些循环？）
我认为我需要的是：
mydf[, c("Exp"):= sum(Ind), by = c("Name")][Year < Year & Year >= Yearm5]
给出：
Empty data.table (0 rows) of 5 cols: Year,Name,Ind,Yearm5,Exp
只使用一个条件
mydf1 <- mydf[, c("Exp"):= sum(Ind), by = c("Name")][Year >= Yearm5]
给出了总经验，所以我假设Year < Year条件出了问题。
我不太确定。我也尝试修改以下建议： how to cumulatively add values in one vector in R 如果没有运气，我指定条件的方式似乎有些不对。
library(dplyr)
mytest1 <- mydf %>%
group_by(Name, Year) %>%
filter(Year < Year & Year >= Yearm5) %>%
mutate(Exp = sum(Ind))
结果应如下所示：
myresult <- data.frame (Year = c(2003, 2004, 2004, 2006,
2007, 2000, 2001, 2005,
2005, 2006, 2007, 2000,
2001, 2002, 2002, 2003),
Name = c("Fred", "Fred", "Fred", "Fred",
"Fred", "Gill", "Gill", "Gill",
"Gill", "Gill", "Gill", "Tom",
"Tom", "Tom", "Tom", "Tom"),
Ind = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1),
Exp = c(0, 1, 1, 3, 4, 0, 1, 1, 1, 2, 3, 0, 1, 2, 2, 4),
Yearm5 = c(1998, 1999, 1999, 2001, 2002,
1995, 1996, 2000, 2000, 2001,
2002, 1995, 1996, 1996, 1997, 1998))
任何帮助或指示都将不胜感激！
答案 0 :(得分：3)
此处使用data.table进行了roll更多方法。
setDT(mydf)
# this is our desired end point
boundary = mydf[, list(Name, year.end = Year + 4)]
# set the key for the following merges
setkey(mydf, Name, Year)
setkey(boundary, Name, year.end)
# add indices that will keep track of the positions to compute deltas
mydf[, idx := .I]
boundary[, idx := .I]
# merge, rolling to match the end correctly, and then subtract the indices
# to get the desired delta.
# Note that we need to unique data because of duplicates.
# Depending on data you may also need to add `allow.cartesian = TRUE`.
# Final note - in data.table <= 1.9.2 you should omit the `by = .EACHI` part.
mydf[unique(boundary)[unique(mydf), list(Exp = i.idx - idx),
roll = -Inf, by = .EACHI]]
# Year Name idx Exp
# 1: 2003 Fred 1 0
# 2: 2004 Fred 2 1
# 3: 2004 Fred 3 1
# 4: 2006 Fred 4 3
# 5: 2007 Fred 5 4
# 6: 2000 Gill 6 0
# 7: 2001 Gill 7 1
# 8: 2005 Gill 8 1
# 9: 2005 Gill 9 1
#10: 2006 Gill 10 2
#11: 2007 Gill 11 3
#12: 2000 Tom 12 0
#13: 2001 Tom 13 1
#14: 2002 Tom 14 2
#15: 2002 Tom 15 2
#16: 2003 Tom 16 4
答案 1 :(得分：2)
使用data.table，我认为您要查找的语法应该是这样的：
setDT(mydf)
mydf[ , Exp := rank(x=Year,ties.method="min")-1, by=Name]
答案 2 :(得分：2)
以下是使用rollapply和data.table
library(zoo)
setDT(mydf)
setkey(mydf, Name,Year)
# create a data.table that has all Years and incidences including the 5 year window
# and sum up the number of incidences per year for each subject
m <- mydf[CJ(unique(Name),seq(min(Year)-5, max(Year))),allow.cartesian=TRUE][,
list(Ind = unique(Ind), I2 = sum(Ind,na.rm=TRUE)),
keyby=list(Name,Year)]
# use rollapply over this larger data.table to get the number of
# incidences in the previous 5 years (not including this year (hence head(x,-1))
m[,Exp := rollapply(I2, 5, function(x) sum(head(x,-1)),
align = 'right', fill=0),by=Name]
# join with the original to create your required data
m[mydf,!c('I2'),with=FALSE]
Name Year Ind Exp
# 1: Fred 2003 1 0
# 2: Fred 2004 1 1
# 3: Fred 2004 1 1
# 4: Fred 2006 1 3
# 5: Fred 2007 1 4
# 6: Gill 2000 1 0
# 7: Gill 2001 1 1
# 8: Gill 2005 1 1
# 9: Gill 2005 1 1
# 10: Gill 2006 1 2
# 11: Gill 2007 1 3
# 12: Tom 2000 1 0
# 13: Tom 2001 1 1
# 14: Tom 2002 1 2
# 15: Tom 2002 1 2
# 16: Tom 2003 1 4