英文:
New columns in data.frame don't retain POSIXct class
问题
我花了将近两天的时间来找出错误发生的原因 - 对许多人来说可能很微不足道，但我无法弄清楚这个原因，我对帮助感到感激：
当我创建一个新的数据框并使用...$...语法添加具有特定类（POSIXct）的列时，它可以正常工作（下面的代码中的“p”列，它们变成了预期的POSIXct类）。
然而，如果我使用...[..., ...]语法执行相同的操作，那么在赋值时，POSIXct类会丢失（下面代码中的“n”列，因为它们意外地变成了数值类）。
即使明确设置了类，使用...[..., ...]语法仍然保持为数值类，但不是使用...$....语法。。
这种行为背后的原因是什么？显然，我已经找到了一种解决方法，但使用列名称的向量更方便，我担心我可能错过了一些非常基本的东西，但无法弄清楚是什么，或者在哪里查找关键字。
基本上，我需要通过一个变量访问列，然后分配类和数据。
rm(dfDummy) # 确保没有残留的旧数据/列
dfDummy <- data.frame(a = 1:10, dummy = dummy)
dfDummy$p <- as.POSIXct(NA)
dfDummy$p.rep <- as.POSIXct(rep(NA, 10))
dfDummy[ , c("n1", "n2")] <- as.POSIXct(NA)
dfDummy[ , c("n1.rep", "n2.rep")] <- as.POSIXct(rep(NA, 10))
sapply(X = c("p", "p.rep", "n1", "n2", "n1.rep", "n2.rep"), function(x) class(dfDummy[, x]))
# 即使明确设置类，它仍然是“numeric” - 这里有什么问题？
class(dfDummy[ , c("n1", "n2", "n1.rep", "n2.rep")]) <- c("POSIXct", "POSIXt")
sapply(X = c("p", "p.rep", "n1", "n2", "n1.rep", "n2.rep"), function(x) class(dfDummy[, x]))
英文:
I spent almost two days to find the reason of an error occuirring - probably trivial for many, but I cannot figure out the reason for that and I am thankful for help:
When I create a new data.frame and add columns with a specific class (POSIXct) using ...$... syntax, it works nicely ("p" columns in code below, they become class POSIXct as intended).
However, if I do the same using the ...[..., ...] syntax, POSIXct class is lost upon assignment ("n" columns in code below, since they become unintendedly class numeric).
Even after setting class explicitely, it remains numeric using the ...[..., ...] syntax, but not using the ...$.... syntax..
What is the reasoning behind this behaviour? Obviously I have found a workaround, but it is more convenient to use vectors of column names, and I am afraid that I miss sth. very basic but cannot figure out what, or where to look by which keywords.
Basically I need to access the columns by a variable and then assign class and data.
rm(dfDummy) # just make sure there is no residual old data/columns leftover
dfDummy <- data.frame(a = 1:10, dummy = dummy)
dfDummy$p <- as.POSIXct(NA)
dfDummy$p.rep <- as.POSIXct(rep(NA, 10))
dfDummy[ , c("n1", "n2")] <- as.POSIXct(NA)
dfDummy[ , c("n1.rep", "n2.rep")] <- as.POSIXct(rep(NA, 10))
sapply(X = c("p", "p.rep", "n1", "n2", "n1.rep", "n2.rep"), function(x) class(dfDummy[, x]))
# even after setting the class explicitely, it remains "numeric" - what is wrong?
class(dfDummy[ , c("n1", "n2", "n1.rep", "n2.rep")]) <- c("POSIXct", "POSIXt")
sapply(X = c("p", "p.rep", "n1", "n2", "n1.rep", "n2.rep"), function(x) class(dfDummy[, x]))
答案1
得分: 1
这个问题与使用$或[实际上没有太大关系，除非使用$时分配单列，而使用[时分配多列。
当你将值分配给多列时，POSIXct向量会被循环使用并简化为一个矩阵，而矩阵无法保存POSIXct类。
如果你改为传递一个列表，它会起作用：
dfDummy[, c("n1.rep", "n2.rep")] <- list(as.POSIXct(NA))
lapply(dfDummy[, c("n1.rep", "n2.rep")], class)
$n1.rep
[1] "POSIXct" "POSIXt"
$n2.rep
[1] "POSIXct" "POSIXt"
英文:
The issue has nothing really to do with using $ or [, except when using $ a single column is being assigned and when you're using [ multiple columns are.
Rather when you assign into multiple columns the POSIXct vector is being recycled and simplified into a matrix - and matrices can't hold class POSIXct.
If you instead pass a list, it will work:
dfDummy[ , c("n1.rep", "n2.rep")] <- list(as.POSIXct(NA))
lapply(dfDummy[ , c("n1.rep", "n2.rep")], class)
$n1.rep
[1] "POSIXct" "POSIXt"
$n2.rep
[1] "POSIXct" "POSIXt"
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