更新 data.table
版本1.8.0及更高版本此问题不再适用。来自新闻档案:
现在允许在键中使用字符列,并且首选 因子。 data.table()和setkey()不再强制出现字符 因子。仍然支持因素。实现FR#1493,FR#1224 和(部分)FR#951。
原始问题
我尝试加入两个data.tables。但是,连接的成功取决于我用来匹配data.tables的列的类。更确切地说,似乎列不应该具有类“字符”。我不太明白原因,但我确定我在这里遗漏了一些明显的东西。所以非常感谢帮助。
以下是一个例子:
#Objective: Select all rows from DT for which Region=="US", Year >= 5 & Year<=8, Cat="A"
library(data.table)
#Set-up data.table DT
DT <- data.table(Year=1:20, value=rnorm(20), Region=c(rep("US", 10), rep("EU", 10)), Cat=c(rep("A", 7), rep("B", 7), rep("C", 6)))
setkey(DT, Region, Cat, Year)
#Set-up data.table int_DT to join with DT
years <- 5:8
df <- data.frame(Region=c("US", "EU"), Categ=c("A", "B"))
int_DT <- J(cbind(df[1, ], years))
#Join them: Works like a charm!
DT[int_DT]
#Let's assume that for any reason the columns in df are of class "character"
df$Region <- as.character(df$Region)
df$Categ <- as.character(df$Categ)
#Rebuild int_DT
int_DT <- J(cbind(df[1, ], years))
DT[int_DT]
#Error in `[.data.table`(DT, int_DT) :
# unsorted column Region of i is not internally type integer.
#OK, maybe the problem is that the column classes in DT are factors, so change those:
DT[, Cat:=as.character(Cat)]
DT[, Region:=as.character(Region)]
DT[int_DT]
#Error in `[.data.table`(DT, int_DT) :
# When i is a data.table, x must be sorted to avoid a vector scan of x per row of i
仍然无效。为什么?有什么限制?我错过了什么?另外信息:我在平台上使用data.table 1.6.6和R版本2.13.2(2011-09-30):x86_64-pc-linux-gnu(64位)。
答案 0 :(得分:3)
您无需连接操作即可获得所需的结果。你说: '目标:从DT中选择Region ==“US”,Year&gt; = 5&amp;的所有行。年&lt; = 8,Cat =“A”'
DT[Region=="US" & Year>=5 & Year <= 8 & Categ=="A"]
Year value Region Categ
[1,] 5 -0.18631697 US A
[2,] 6 1.40059083 US A
[3,] 7 0.01848557 US A
但要回答关于列类的问题。我设法让这段代码工作,这实际上反映了上面的代码:
> setkey(DT, Region, Categ, Year)
> df <- data.frame(Region=c("US", "EU"), Categ=c("A", "B"))
> dt2 <- data.table(data.frame(df[1, ], Year=5:8))
Warning message:
In data.frame(df[1, ], Year = 5:8) :
row names were found from a short variable and have been discarded
> dt1[dt2]
Region Categ Year value
[1,] US A 5 -0.5565422
[2,] US A 6 -0.1805841
[3,] US A 7 1.4474403
[4,] US A 8 NA
同样,列类为character
:
df$Region <- as.character(df$Region)
df$Categ <- as.character(df$Categ)
#Rebuild int_DT
dt2 <- J(cbind(df[1, ], Year=5:8))
Warning message:
In data.frame(..., check.names = FALSE) :
row names were found from a short variable and have been discarded
setkey(dt2, Region)
dt1[dt2]
Region Year value Categ Categ.1 Year.1
US 1 1.20152558 A A 5
US 2 1.89391079 A A 5
US 3 -1.76022634 A A 5
US 4 0.92454680 A A 5
US 5 -0.55654217 A A 5
...
snip
...
US 9 0.67936243 B A 8
US 10 -0.09355764 B A 8