由于（仍然）没有人得到复选标记，我假设您考虑了一些实际问题，主要是因为您没有指定要转换为的向量类型numeric。我建议你应该申请transform功能以完成您的任务。
现在我要演示某些“转换异常”：
# create dummy data.frame
d <- data.frame(char = letters[1:5],
fake_char = as.character(1:5),
fac = factor(1:5),
char_fac = factor(letters[1:5]),
num = 1:5, stringsAsFactors = FALSE)
让我们看一下data.frame
> d
char fake_char fac char_fac num
1 a 1 1 a 1
2 b 2 2 b 2
3 c 3 3 c 3
4 d 4 4 d 4
5 e 5 5 e 5
让我们运行：
> sapply(d, mode)
char fake_char fac char_fac num
"character" "character" "numeric" "numeric" "numeric"
> sapply(d, class)
char fake_char fac char_fac num
"character" "character" "factor" "factor" "integer"
现在你可能会问自己“异常在哪里？”嗯，我在 R 中遇到了非常奇怪的事情，而这不是the最令人困惑的事情，但它可能会让你感到困惑，特别是如果你在上床睡觉之前读到这篇文章。
Here goes: first two columns are character. I've deliberately called 2nd one fake_char. Spot the similarity of this character variable with one that Dirk created in his reply. It's actually a numerical vector converted to character. 3rd and 4th column are factor, and the last one is "purely" numeric.
如果您使用transform函数，您可以将fake_char into numeric，但不是char变量本身。
> transform(d, char = as.numeric(char))
char fake_char fac char_fac num
1 NA 1 1 a 1
2 NA 2 2 b 2
3 NA 3 3 c 3
4 NA 4 4 d 4
5 NA 5 5 e 5
Warning message:
In eval(expr, envir, enclos) : NAs introduced by coercion
但如果你做同样的事情fake_char and char_fac，你会很幸运，并且不会出现 NA 的情况：
> transform(d, fake_char = as.numeric(fake_char),
char_fac = as.numeric(char_fac))
char fake_char fac char_fac num
1 a 1 1 1 1
2 b 2 2 2 2
3 c 3 3 3 3
4 d 4 4 4 4
5 e 5 5 5 5
如果保存转换后的data.frame并检查mode and class， 你会得到：
> D <- transform(d, fake_char = as.numeric(fake_char),
char_fac = as.numeric(char_fac))
> sapply(D, mode)
char fake_char fac char_fac num
"character" "numeric" "numeric" "numeric" "numeric"
> sapply(D, class)
char fake_char fac char_fac num
"character" "numeric" "factor" "numeric" "integer"
所以，结论是：是的，您可以转换character向量化为numeric一，但前提是它的元素可以“转换”为numeric.
