我对 OLapCube 包 data.cube 有一些问题:
install.packages("data.cube", repos = paste0("https://", c(
"jangorecki.gitlab.io/data.cube",
"cloud.r-project.org"
)))
部分测试数据:
library(data.table)
set.seed(42)
dt <- CJ(color = c("green","yellow","red"),
year = 2011:2015,
month = 1:12,
status = c("active","inactive","archived","removed")
)[sample(600)]
dt[, "value" := sample(4:7/2, nrow(dt), TRUE)]
现在我想创建一个多维数据集并在时间维度上应用层次结构。像这样的东西:
library(data.cube)
dc <- as.data.cube(dt, id.vars = c("color", "year", "month", "status"),
measure.vars = "value",
hierarchies = list(time <- list("year, month")))
如果我运行此代码，我会收到错误消息:
Error in as.data.cube.data.table(dt, id.vars = c("color", "year", "month", :
identical(names(hierarchies), id.vars) | identical(names(hierarchies), .... is not TRUE
如果我尝试类似的东西
hierarchies = list(time <- list("year, month"), color <- list("color"),
status <- list("status"))
我犯了同样的错误。
最佳答案
写得很好的问题。
我看到您根据 ?as.data.cube 示例制作了示例，因此我也会尝试使用该示例来回答您的问题
# Original example goes as follows
library(data.cube)
library(data.table)
set.seed(1L)
dt = CJ(color = c("green","yellow","red"),
year = 2011:2015,
status = c("active","inactive","archived","removed"))[sample(30)]
dt[, "value" := sample(4:7/2, nrow(dt), TRUE)]
dc = as.data.cube(
x = dt, id.vars = c("color","year","status"),
measure.vars = "value",
hierarchies = sapply(c("color","year","status"),
function(x) list(setNames(list(character()), x)),
simplify=FALSE)
)
str(dc)
检查层次结构的有效性时，您的错误似乎被提出。
不幸的是，这不是很有意义的错误，我创建了问题 #18，所以有一天会得到改进。
因此，让我们比较手册中的层次结构和示例中创建的层次结构。
sapply(c("color","year","status"),
function(x) list(setNames(list(character()), x)),
simplify=FALSE) -> h
str(h)
#List of 3
# $ color :List of 1
# ..$ :List of 1
# .. ..$ color: chr(0)
# $ year :List of 1
# ..$ :List of 1
# .. ..$ year: chr(0)
# $ status:List of 1
# ..$ :List of 1
# .. ..$ status: chr(0)
hierarchies = list(time <- list("year, month"), color <- list("color"),
status <- list("status"))
str(hierarchies)
#List of 3
# $ :List of 1
# ..$ : chr "year, month"
# $ :List of 1
# ..$ : chr "color"
# $ :List of 1
# ..$ : chr "status"
我们可以看到手册中的层次结构是命名元素的列表，而您的示例是未命名元素的列表。
我相信你在应该使用
<- 的地方误用了 =。 <- 并不总是等于 = 运算符。您可以在 3.1.3.1 Assignment <- vs = 中阅读有关这种情况的更多信息。所以让我们看看修复是否足够
hierarchies = list(time = list(c("year, month")), color = list("color"),
status = list("status"))
dc <- as.data.cube(dt, id.vars = c("color", "year", "month", "status"),
measure.vars = "value",
hierarchies = hierarchies)
我们仍然有同样的错误，所以需要命名，而这不是问题的根本原因。仔细观察后，我现在看到您想要构建没有主键的时间维度。
重要说明，您不能将多个列名作为单个字符串传递，因此
"year, month"
应该写成
c("year","month")
我们仍然需要时间维度主键是单个字段，其中年和月将只是属性。
因此，让我们为时间维度创建主键，因为我们的时间维度具有年-月粒度，我们将在该粒度上创建键。
library(data.table)
set.seed(42)
dt <- CJ(color = c("green","yellow","red"),
year = 2011:2015,
month = 1:12,
status = c("active","inactive","archived","removed")
)[sample(600)
][, yearmonth:=sprintf("%04d%02d", year, month) # this ensure four numbers for year and 2 numbers for month
]
dt[, "value" := sample(4:7/2, nrow(dt), TRUE)]
现在让我们做层次结构，注意
year 已更改为 yearmonth 。在下面的层次结构中，值向量
c("year","month") 意味着这些属性依赖于 yearmonth 。有关更复杂的层次结构情况，请参阅 ?as.data.cube 中的更多示例。hierarchies = list(
color = list(color = list(color = character())),
yearmonth = list(yearmonth = list(yearmonth = c("year","month"))),
status = list(status = list(status = character()))
)
dc = as.data.cube(
x = dt, id.vars = c("color","yearmonth","status"),
measure.vars = "value",
hierarchies = hierarchies
)
str(dc)
我们的
data.cube 已经成功创建。让我们尝试使用 yearmonth 的键来查询它dc[, .(yearmonth=201105L)] -> d
as.data.table(d)
dc[, .(yearmonth=201105L), drop=FALSE] -> d
as.data.table(d)
现在尝试使用维度、年和月的属性来查询它
dc[, .(year=2011L)] -> d
as.data.table(d) # note that dimension is not being dropped because it still have more than 1 value
dc[, .(month=5L)] -> d
as.data.table(d)
dc[, .(year=2011L, month=5L)] -> d
as.data.table(d) # here dimension has been dropped because there was only single element in that dimension, you can of course use `drop=FALSE` if needed.
希望能帮到你，祝你好运!
关于R 数据立方体定义层次结构，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/52816087/