我在R中有一个查找表,我试图弄清楚如何实现。我面临的挑战是它涉及连续的数值或数据范围。如果值介于两者之间我希望选择正确的值。
我想使用两个连续的'GRADE','SAT'变量加上分类'TYPE'值来分配'GROUP'值。这一大块代码看起来令人生畏,但这些都是微不足道的小桌子。
任何建议都值得赞赏!!!!
#lookup table code for recreating dataframe
structure(list(Type = structure(c(1L, 2L, 1L, 1L), .Label = c("A",
"B"), class = "factor"), min_grade = c(93L, 85L, 93L, 80L), max_grade = c(100L,
93L, 100L, 92L), min_sat = c(600L, 700L, 400L, 600L), max_sat = c(800L,
800L, 599L, 800L), Group = structure(c(1L, 1L, 2L, 3L), .Label = c("A",
"B", "C"), class = "factor")), .Names = c("Type", "min_grade",
"max_grade", "min_sat", "max_sat", "Group"), class = "data.frame", row.names = c(NA,
-4L))
#example ----- desired value is in the 'GROUP' column so this would be NULL before I used the lookup table
structure(list(Name = structure(c(3L, 1L, 2L, 4L), .Label = c("Jack",
"James", "John", "Jordan"), class = "factor"), Grade = c(95L,
95L, 92L, 93L), Sat = c(701L, 500L, 800L, 800L), Type = structure(c(1L,
1L, 1L, 2L), .Label = c("A", "B"), class = "factor"), Group = structure(c(1L,
2L, 3L, 1L), .Label = c("A", "B", "C"), class = "factor")), .Names = c("Name",
"Grade", "Sat", "Type", "Group"), class = "data.frame", row.names = c(NA,
-4L))
答案 0 :(得分:1)
这是怎么回事?
ltab <- structure(list(Type = structure(c(1L, 2L, 1L, 1L), .Label = c("A",
"B"), class = "factor"), min_grade = c(93L, 85L, 93L, 80L), max_grade = c(100L,
93L, 100L, 92L), min_sat = c(600L, 700L, 400L, 600L), max_sat = c(800L,
800L, 599L, 800L), Group = structure(c(1L, 1L, 2L, 3L), .Label = c("A",
"B", "C"), class = "factor")), .Names = c("Type", "min_grade",
"max_grade", "min_sat", "max_sat", "Group"), class = "data.frame", row.names = c(NA,
-4L))
dat <- structure(list(Name = structure(c(3L, 1L, 2L, 4L), .Label = c("Jack",
"James", "John", "Jordan"), class = "factor"), Grade = c(95L,
95L, 92L, 93L), Sat = c(701L, 500L, 800L, 800L), Type = structure(c(1L,
1L, 1L, 2L), .Label = c("A", "B"), class = "factor")), .Names = c("Name",
"Grade", "Sat", "Type"), class = "data.frame", row.names = c(NA,
-4L))
library(plyr)
mdat <- adply(merge(dat, ltab, by="Type", all=T), 1, function(x) {
c(FallsIn=x$Grade > x$min_grade & x$Grade <= x$max_grade & x$Sat > x$min_sat & x$Sat <= x$max_sat)
})
mdat[mdat$FallsIn,]
考虑概括,是否会有更多连续变量需要检查?
编辑:无法编辑OP帖子,因此考虑OP的评论是我如何处理&#34;对多维连续随机变量进行分类的一个例子&#34; 这样,这些关键字将在未来的搜索中标记breaks <- list(Var1=c(0, 0.25, 1),
Var2=c(0, 0.5, 1),
Var3=c(0, 0.25, 0.75, 1))
#generate this on the fly
genIntv <- function(x) {
ret <- paste0("(", x[1:(length(x)-1)],", ",x[2:length(x)], "]")
names(ret) <- 1:(length(x)-1)
ret
}
lookupTbl <- data.frame(expand.grid(lapply(breaks, genIntv), stringsAsFactors=F),
Group=LETTERS[1:12])
lookupTbl2 <- data.frame(expand.grid(lapply(breaks, function(x) 1:(length(x)-1)), stringsAsFactors=F),
Group=LETTERS[1:12])
#data set
dat <- data.frame(Var1=c(0.1, 0.76), Var2=c(0.5, 0.75), Var3=c(0.25,0.9))
binDat <- do.call(cbind, setNames(lapply(1:ncol(dat), function(k)
.bincode(dat[,k], breaks[[k]], T, T)),colnames(dat)))
merge(binDat, lookupTbl2, all.x=T, all.y=F)
如果其他人有更好的方法,那就太好了解
答案 1 :(得分:0)
如果你的数据很小,那么完整的连接应该没问题。
library(dplyr)
result =
example %>%
select(-Type) %>%
full_join(look_up) %>%
filter(min_grade < Grade & Grade <= max_grade &
min_sat < Sat & Sat <= max_sat)