英文:
replace NA in multiple columns of different classes
问题
我有多列类似名称的数据，但属于不同的类别。我需要用0替换所有的NA，但保留列的类别，因为稍后会为不同的字符串分配其他数值。
这是示例数据：
tricep_wt = c(2,NA,3))```
这是我尝试将NA更改为0的方法：
mutate(qdf, across(contains("wt"), ~case_when(is.numeric(.x) ~ tidyr::replace_na(., 0),
is.character(.x) ~ tidyr::replace_na(., "0"))))
我收到错误：
Error in mutate():
i In argument: across(...).
Caused by error in across():
! Can't compute column bicep_wt.
Caused by error in case_when():
! Failed to evaluate the right-hand side of formula 1.
Caused by error in vec_assign():
! Can't convert replace <double> to match type of data <character>.
使用相同的方法也会出现错误：
mutate(qdf, across(contains("wt"), ~case_when(is.numeric(.x) ~ tidyr::replace_na(.x, 0),
is.character(.x) ~ tidyr::replace_na(.x, "0"))))
<details>
<summary>英文:</summary>
I have data with multiple columns of similar names, but of different classes. I need to replace all `NA` with `0` but retain the columns class, as different character strings will be assigned other numeric values later.
This is example data:
qdf = data.frame(bicep_wt = c("black band", "5", NA),
tricep_wt = c(2,NA,3))
and this is my attempt to change the NA to 0:
mutate(qdf, across(contains("wt"), ~case_when(is.numeric(.x) ~ tidyr::replace_na(., 0),
is.character(.x) ~ tidyr::replace_na(., "0"))))
I get error:
Error in mutate():
i In argument: across(...).
Caused by error in across():
! Can't compute column bicep_wt.
Caused by error in case_when():
! Failed to evaluate the right-hand side of formula 1.
Caused by error in vec_assign():
! Can't convert replace <double> to match type of data <character>.
same error with:
mutate(qdf, across(contains("wt"), ~case_when(is.numeric(.x) ~ tidyr::replace_na(.x, 0),
is.character(.x) ~ tidyr::replace_na(.x, "0"))))
</details>
# 答案1
**得分**: 2
以下是翻译好的部分：
"While being 'class-safe' is usually a good thing, functions that are not class-safe can be used advantageously."
"虽然通常来说，具有“类安全性”通常是一件好事，但那些不具备类安全性的函数也可以有优势的用途。"
By "class-safe", I mean that you are guaranteed of the class returns from an expression. For instance,
"所谓“类安全性”，指的是你可以从表达式中得到类别安全的返回值。例如，"
The first call is ambiguous, since the `yes=` is class numeric and the `no=` is class character. A class-safe function should complain about this, as in
"第一个调用是模糊的，因为`yes=`的类别是数值，而`no=`的类别是字符。一个具备类安全性的函数应该会抱怨这一点，如下所示："
Note that `ifelse` and `replace` are _not_ class-safe, but in this case it is acceptable based on your requirements.
"请注意，`ifelse` 和 `replace` _不具备_ 类安全性，但在这种情况下，根据您的需求，这是可以接受的。"
<details>
<summary>英文:</summary>
While being "class-safe" is usually a good thing, functions that are not class-safe can be used advantageously.
```r
mutate(qdf, across(contains("wt"), ~ replace(.x, is.na(.x), 0)))
# bicep_wt tricep_wt
# 1 black band 2
# 2 5 0
# 3 0 3
By "class-safe", I mean that you are guaranteed of the class returns from an expression. For instance,
ifelse(c(T, T), 1, "1")
# [1] 1 1
ifelse(c(T, F), 1, "1")
# [1] "1" "1"
The first call is ambiguous, since the yes= is class numeric and the no= is class character. A class-safe function should complain about this, as in
dplyr::if_else(c(T, T), 1, "1")
# Error in dplyr::if_else(c(T, T), 1, "1") :
# Can't combine `true` <double> and `false` <character>.
data.table::fifelse(c(T, T), 1, "1")
# Error in data.table::fifelse(c(T, T), 1, "1") :
# 'yes' is of type double but 'no' is of type character. Please make sure that both arguments have the same type.
Note that ifelse and replace are not class-safe, but in this case it is acceptable based on your requirements.
答案2
得分: 1
你可以将条件传递给 replace_na 函数的内部：
mutate(qdf, across(contains("wt"), ~ replace_na(.x, `if`(is.numeric(.x), 0, "0"))))
结果：
bicep_wt tricep_wt
1 black band 2
2 5 0
3 0 3
注：它可以使用 ifelse() 或 `if`()。
英文:
You can pass the condition to inside replace_na:
mutate(qdf, across(contains("wt"), ~ replace_na(.x, `if`(is.numeric(.x), 0, "0"))))
Result:
bicep_wt tricep_wt
1 black band 2
2 5 0
3 0 3
Obs: it works with either ifelse() or `if`().
答案3
得分: 0
mutate(
qdf,
across(
contains("wt"),
(.x) { # could use ~ instead
if (is.numeric(.x)) tidyr::replace_na(.x, 0)
else if (is.character(.x)) tidyr::replace_na(.x, "0")
}
)
)
bicep_wt tricep_wt
1 black band 2
2 5 0
3 0 3
英文:
mutate(
qdf,
across(
contains("wt"),
\(.x) { # could use ~ instead
if (is.numeric(.x) ) tidyr::replace_na(.x, 0)
else if (is.character(.x)) tidyr::replace_na(.x, "0")
}
)
)
# bicep_wt tricep_wt
# 1 black band 2
# 2 5 0
# 3 0 3
答案4
得分: 0
- 用循环的方式：
for (col in colnames(qdf)) {
qdf[is.na(qdf[, col]), col] <- 0
}
- 使用函数和
lapply()：
naToZero <- function(v) {
v[is.na(v)] <- 0
return(v)
}
qdf <- data.frame(lapply(X=qdf, FUN=function(u) naToZero(u)))
qdf
bicep_wt tricep_wt
1 black band 2
2 5 0
3 0 3
英文:
If you don't know that your columns will be only numeric or character, you can do a version that will substitute the correct type of NA no matter what.
1) With a loop
for (col in colnames(qdf)) {
qdf[is.na(qdf[, col]), col] <- 0
}
2) With a function and lapply()
naToZero <- function(v) {
v[is.na(v)] <- 0
return(v)
}
qdf <- data.frame(lapply(X=qdf, FUN=function(u) naToZero(u)))
qdf
bicep_wt tricep_wt
1 black band 2
2 5 0
3 0 3
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