在新R版本中以旧版本编写的代码编译问题 [英] Problems compiling code written in old version in new R version
问题描述
我在新版本的R（4.0.1；平台：x86_64-w64-mingw32 / x64（64位））和RStudio（1.3.959版）中运行命令时遇到问题，在旧版本的R
I am having trouble running commands in new version of R (4.0.1; Platform: x86_64-w64-mingw32/x64 (64-bit)) and RStudio (Version 1.3.959) which worked well in the older version of R.
比方说，我有一个名为Check的表，其中包含10,000多行和100多个变量（分类和数字）。
Let's say, I have a table named Check with more than 10,000 rows and more than 100 variables (categorical and numeric).
如果我尝试调用droplevels命令，得到以下消息。
If I try to invoke the droplevels command, I get the below message.
Check <- droplevels(Check)
Error in .shallow(x, cols = cols, retain.key = TRUE) :
can't set ALTREP truelength
，下面的方法
Check <- rapply(Check, f = droplevels, classes = "factor", how = "replace")
当我尝试通过定义新级别并将其替换为NA来替换类别变量中的NA时，我得到了下面的消息：
When I try to replace the NA's in a categorical variable by defining a new level and replacing it for NA's, I get the below message:
levels(Check$A) <- c(levels(Check$A), 'unknown.')
# Check$A <- factor(Check$A, levels=c(levels(Check$A), 'unknown.'))
Check$A[is.na(Check$A)] <- 'unknown.'
Error in setalloccol(newx) : can't set ALTREP truelength
当我尝试打开表格时，出现以下消息：
When I try to open the table, I get the below message:
View(Check)
Error in view: can't set ALTREP truelength
我不明白这里出了什么问题。
I do not understand what has seriously gone wrong here. Any idea please?
我尝试过玩
library(tidyverse)
Check <- data.frame(col1 = c(NA, letters[1:10]), col2 = c(NA, NA, 1:8, NA),
col3 = c(NA, letters[1:5], NA, NA, NA, NA, NA))
Test <- Check
Test <- droplevels(Test)
str(Test)
Test2 <- Test[6:11,]
Test2 <- Test2 %>% mutate_if(sapply(Test2, is.character), as.factor)
Test2 <- droplevels(Test2)
上面的方法工作正常，并使用 dput（Test2）收益
The above works fine and using dput(Test2) yields
structure(list(col1 = structure(c(NA, 1L, 2L, 3L, 4L, 5L, 6L,
7L, 8L, 9L, 10L), .Label = c("a", "b", "c", "d", "e", "f", "g",
"h", "i", "j"), class = "factor"), col2 = c(NA, NA, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, NA), col3 = structure(c(6L, 1L, 2L, 3L, 4L,
5L, 6L, 6L, 6L, 6L, 6L), .Label = c("a", "b", "c", "d", "e",
"unknown."), class = "factor")), row.names = c(NA, -11L), class = "data.frame")
但是，对于我的数据，我得到了一些东西最终使用dput这样，尽管我没有使用data.table。
However, for my data, I get something like this in the end using dput, though I am not using data.table.
row.names = c(NA,
-5L), .internal.selfref = <pointer: 0x0000000004f81ef0>, class = c("data.table",
"data.frame"))
当我成功地尽快完成数据时，我试图模仿我的数据并将其摆出。
I am trying to imitate my data and shall pose it, when I am successful in doing it asap.
推荐答案
下面的示例运行正常，没有任何问题：
The below example runs fine without any problem:
library(tidyverse)
library(data.table)
Check <- data.frame(col1 = c(NA, letters[1:10]), col2 = c(NA, NA, 1:8, NA),
col3 = c(NA, letters[1:5], NA, NA, NA, NA, NA))
Test1 <- Check
dput(Test1)
Test2 <- as.data.table(Check) # Convert to data.table
dput(Test2)
Test1 <- droplevels(Test1)
str(Test1)
Test1 <- Test1 %>% dplyr::mutate_if(sapply(Test1, is.character), as.factor)
Test1 <- Test1 %>% dplyr::mutate_if(sapply(Test1, is.integer), as.numeric)
str(Test1)
Test1 <- droplevels(Test1)
Test2 <- droplevels(Test2)
str(Test2)
Test2 <- Test2 %>% dplyr::mutate_if(sapply(Test2, is.character), as.factor)
Test2 <- Test2 %>% dplyr::mutate_if(sapply(Test2, is.integer), as.numeric)
str(Test2)
Test2 <- droplevels(Test2)
现在来看这个例子：
library(tidyverse)
library(data.table)
Check1 <- data.frame(col1 = c(NA, letters[1:200]), col2 = c(NA, NA, 1:198, NA),
col3 = c(NA, letters[1:195], NA, NA, NA, NA, NA),
col4 = c(NA, NA, letters[1:199]), col5 = c(NA, letters[7:206]),
col6 = c(NA, NA, letters[1:198], NA),
col7 = c(NA, letters[1:197], NA, NA, NA),
col8 = c(NA, letters[4:203]),
col9 = c(NA, letters[6:205]),
col10 = c(letters[1:200], NA),
col11 = c(NA, NA, letters[1:197], NA, NA),
col12 = c(NA, letters[2:201]),
col13 = c(NA, NA, NA, NA, NA, letters[1:196]) )
Check2 <- data.frame(replicate(100,sample(0:1000,201,rep=TRUE)))
Check <- cbind(Check1, Check2)
Test1 <- Check
dput(Test1)
# dput gives ,row.names = c(NA, -201L), class = "data.frame")
Test2 <- as.data.table(Check)
dput(Test2)
# dput gives row.names = c(NA, -201L), .internal.selfref = <pointer: 0x00000000052e1ef0>, class # = c("data.table", "data.frame"))
# The below block runs without any problem since Test1 is of class data.frame
Test1 <- droplevels(Test1)
str(Test1)
Test1 <- Test1 %>% dplyr::mutate_if(sapply(Test1, is.character), as.factor)
Test1 <- droplevels(Test1)
Test1 <- Test1 %>% dplyr::mutate_if(sapply(Test1, is.integer), as.numeric)
str(Test1)
Test1 <- droplevels(Test1)
# The below block gives problem since Test2 is of class = c("data.table", "data.frame")
Test2 <- droplevels(Test2)
str(Test2)
Test2 <- Test2 %>% dplyr::mutate_if(sapply(Test2, is.character), as.factor)
Test2 <- droplevels(Test2)
Test2 <- Test2 %>% dplyr::mutate_if(sapply(Test2, is.integer), as.numeric)
str(Test2)
Test2 <- droplevels(Test2)
运行前4行的以下错误消息：
I get the following error message running the first 4 lines:
Error in in .shallow(x, cols = cols, retain.key = TRUE) : can't set ALTREP truelength
如果我尝试打开Test2数据框，得到以下消息
If I try to open Test2 data frame, I get the following message
View(Test2)
Error in View : can't set ALTREP truelength
但是，如果是I，请使用
If I, however, delete Test2 using
rm(Test2)
并运行以下命令，我没有收到任何错误：
and run the following, I do not get any error:
Test2 <- as.data.frame(Test2)
str(Test2)
Test2 <- Test2 %>% dplyr::mutate_if(sapply(Test2, is.character), as.factor)
Test2 <- droplevels(Test2)
Test2 <- Test2 %>% dplyr::mutate_if(sapply(Test2, is.integer), as.numeric)
str(Test2)
Test2 <- droplevels(Test2)
-
大小限制是否在data.table中起作用，因为它似乎适用于小数据，并且对上面的示例犹豫不决。
Does size restriction play a role in data.table, since it seems to works for small data and hesitates for the example above.
是否表示每次必须确保将数据另存为类= data.frame的数据框？
Does it mean each time it must be ensured that the data is saved as a data frame with class = "data.frame"?
何时执行此类数据框s会自动转换为data.table，因为在我的真实数据集中，虽然data.table库未加载，但是数据仍保存为data.table？
When do such data frames get converted automatically to data.table, because in my real data set though data.table library is not loaded, despite which, the data is saved as a data.table?
请问任何解释？我已经安装了R 4.0.2，并清理了空间并重新安装了所有软件包和依赖项，而RStudio版本是1.3.959。
Any explanation please? I have R 4.0.2 and swiped the space clean and reinstalled all packages and dependencies fresh, and RStudio version is 1.3.959 .
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