data.table中的列类的限制是什么？ [英] What are the restrictions for the column classes in data.table?
问题描述
UPDATE 此问题与 data.table 版本1.8.0及更高版本无关。从NEWS文件：
UPDATE This problem is not relevant anymore for data.table versions 1.8.0 and higher. From the NEWS file:
字符列现在允许在键中，并且优先于
因子。 data.table（）和setkey（）不再强制字符到
因子。仍然支持因素。实施FR＃1493，FR＃1224
和（部分）FR＃951。
character columns are now allowed in keys and are preferred to factor. data.table() and setkey() no longer coerce character to factor. Factors are still supported. Implements FR#1493, FR#1224 and (partially) FR#951.
strong>
Original question
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，似乎列不应该有类字符。我不太明白的原因，但我相信我错过了一些明显的这里。所以帮助真的很感激。
I try to join two data.tables. However, the success of the join is dependent on the classes of the columns I use to match the data.tables. More precisely, it seems that the columns should not have the class "character". I don't quite understand the reason, but I'm sure I'm missing something obvious here. So help is really appreciated.
以下是一个示例：
#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
仍然不工作。为什么？什么是限制？我错过什么？附加信息：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）。
Still doesn't work. Why? What is the restriction? What do I miss? Additionally information: I'm using data.table 1.6.6 and R version 2.13.2 (2011-09-30) on Platform: x86_64-pc-linux-gnu (64-bit).
推荐答案
您不需要连接操作来获取所需的结果。你说：
'目标：从DT中选择Region ==US，Year> = 5& Year <= 8，Cat =A'
You don't need a join operation to get your desired results. You said: 'Objective: Select all rows from DT for which Region=="US", Year >= 5 & Year<=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
但是回答你关于列类的问题。我设法让这段代码工作，这基本上反映你的代码上面：
But to answer your question about column classes. I managed to get this code to work, which essentially mirrors your code above:
> 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，字符的列类：
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
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