2

我在 R 中使用存储为data.table包含数值和字符类型变量的值更改中获得的值的长表工作。当我想执行一些函数，如相关、回归等时，我必须将表格转换为宽格式并均匀化时间戳频率。

我找到了一种将长表转换为宽表的方法，但我认为效率不高，我想知道是否有更好的更data.table原生的方法。

在下面的可重现示例中，我包含了我发现执行宽低转换的两个选项，并且在评论中我指出了我认为哪些部分不是最佳的。

library(zoo)
library(data.table)
dt<-data.table(time=1:6,variable=factor(letters[1:6]),numeric=c(1:3,rep(NA,3)),
               character=c(rep(NA,3),letters[1:3]),key="time")
print(dt)
print(dt[,lapply(.SD,typeof)])

#option 1

casted<-dcast(dt,time~variable,value.var=c("numeric","character"))
# types are correct, but I got NA filled columns,
# is there an option like drop
# available for columns instead of rows?
print(casted)
print(casted[,lapply(.SD,typeof)])


# This drop looks ugly but I did not figure out a better way to perform it
casted[,names(casted)[unlist(casted[,lapply(lapply(.SD,is.na),all)])]:=NULL]

# I perform a LOCF, I do not know if I could benefit of
# data.table's roll option somehow and avoid
# the temporal memory copy of my dataset (this would be the second
# and minor issue)
casted<-na.locf(casted)

#option2

# taken from http://stackoverflow.com/questions/19253820/how-to-implement-coalesce-efficiently-in-r
coalesce2 <- function(...) {
  Reduce(function(x, y) {
    i <- which(is.na(x))
    x[i] <- y[i]
    x},
    list(...))
}


casted2<-dcast(dt[,coalesce2(numeric,character),by=c("time","variable")],
      time~variable,value.var="V1")
# There are not NA columns but types are incorrect
# it takes more space in a real table (more observations, less variables)
print(casted2)
print(casted2[,lapply(.SD,typeof)])

# Again, I am pretty sure there is a prettier way to do this
numericvars<-names(casted2)[!unlist(casted2[,lapply(
  lapply(lapply(.SD,as.numeric),is.na),all)])]
casted2[,eval(numericvars):=lapply(.SD,as.numeric),.SDcols=numericvars]

# same as option 1, is there a data.table native way to do it?
casted2<-na.locf(casted2)

欢迎在此过程中提供任何建议/改进。

4

1 回答 1

3

我可能会分别做 char 和 num 表，然后 rbind：

k        = "time"
typecols = c("numeric", "character")

res = rbindlist(fill = TRUE, 
  lapply(typecols, function(tc){
    cols = c(k, tc, "variable")
    dt[!is.na(get(tc)), ..cols][, dcast(.SD, ... ~ variable, value.var=tc)]
  })
)

setorderv(res, k)
res[, setdiff(names(res), k) := lapply(.SD, zoo::na.locf, na.rm = FALSE), .SDcols=!k]

这使

   time a  b  c  d  e  f
1:    1 1 NA NA NA NA NA
2:    2 1  2 NA NA NA NA
3:    3 1  2  3 NA NA NA
4:    4 1  2  3  a NA NA
5:    5 1  2  3  a  b NA
6:    6 1  2  3  a  b  c

请注意，OP 的最终结果casted2的不同之处在于它的所有列都为 char。

于 2017-02-17T15:35:51.863 回答