如何在列上使用tidyeval进行突变? [英] How to use tidyeval on a column to mutate?
问题描述
很抱歉造成混乱，但是最终，我发布的第一个示例(在页面底部)并没有帮助我弄清楚tidyeval如何与mutate配合使用，因此我添加了一个新示例./p>
我想创建一个带有三个参数的函数:
- 数据框
- 要突变的列
- 一个变量(来自数据框)，用于替换要变异的值
例如，要将mpg中的值替换为carb中的值，我尝试了以下方法:
I tried this
colToX <- function(dt, ..., repl) {
cols <- quos(...)
repl <- quo(repl)
mutate_at(dt, vars(!!!cols), funs(function(x) !!repl))
}
colToX(mtcars, mpg, repl = carb)
由于以下原因不起作用:
mutate_impl(.data，点)中的错误:不支持列
mpg类型功能
我的第一个示例(为此，@ MrFlick和@UseR都可以正常工作):
例如，下面的一个应mutate()将所有1分配给在...中传递的变量
colTo1 <- function(dt, ...) {
col <- quo(...)
mutate(mtcars, !!col := 1)
}
colTo1(mtcars, mpg)
错误:LHS必须是名称或字符串
最终，输出应与mutate(mtcars, mpg = 1)
@MrFlick的解决方案适用于单列情况，但是由于OP使用...作为参数，因此我认为OP也希望该函数能够分成多列.例如，以下操作将不起作用:
colTo1 <- function(dt, ...) {
col <- quo_name(quo(...))
mutate(dt, !!col := 1)
}
colTo1(mtcars, mpg, cyl)
inherits(x，"quosure")中的错误:找不到对象'cyl'
我们可以做的是使用quos代替quo和mutate_at代替mutate:
colTo1 <- function(dt, ...) {
cols <- quos(...)
mutate_at(dt, vars(!!!cols), function(x) x=1)
}
quos将每个参数从...转换为向量的向量.使用mutate_at的vars语法并使用rlang中的!!!进行显式拼接，我们可以取消引用cols中的每个等价单，并在那些指定的列上进行变异.
现在这可以按预期工作了:
colTo1(mtcars, mpg, cyl)
结果:
mpg cyl disp hp drat wt qsec vs am gear carb
1 1 1 160.0 110 3.90 2.620 16.46 0 1 4 4
2 1 1 160.0 110 3.90 2.875 17.02 0 1 4 4
3 1 1 108.0 93 3.85 2.320 18.61 1 1 4 1
4 1 1 258.0 110 3.08 3.215 19.44 1 0 3 1
5 1 1 360.0 175 3.15 3.440 17.02 0 0 3 2
6 1 1 225.0 105 2.76 3.460 20.22 1 0 3 1
7 1 1 360.0 245 3.21 3.570 15.84 0 0 3 4
8 1 1 146.7 62 3.69 3.190 20.00 1 0 4 2
9 1 1 140.8 95 3.92 3.150 22.90 1 0 4 2
10 1 1 167.6 123 3.92 3.440 18.30 1 0 4 4
...
让"1"成为要传递给函数的另一个参数也很容易:
colToX <- function(dt, ..., X) {
cols <- quos(...)
mutate_at(dt, vars(!!!cols), function(x) x=X)
}
colToX(mtcars, mpg, cyl, X = 2)
编辑:OP更改了问题，要求X应该是同一数据框中的另一列.以下是我的新解决方案:
colToX <- function(dt, ..., X) {
cols <- quos(...)
X_quo <- enquo(X)
mutate_at(dt, vars(!!!cols), funs(.data$`!!`(X_quo)))
}
colToX(mtcars, mpg, cyl, X = hp)
在这里，我正在使用funs函数创建对vars引用的每一列的函数调用列表. .data指的是mutate_at中的输入数据帧(在本例中为dt).我使用enquo将所谓的X转换为quosure，然后使用!!取消引用.
结果:
mpg cyl disp hp drat wt qsec vs am gear carb
1 110 110 160.0 110 3.90 2.620 16.46 0 1 4 4
2 110 110 160.0 110 3.90 2.875 17.02 0 1 4 4
3 93 93 108.0 93 3.85 2.320 18.61 1 1 4 1
4 110 110 258.0 110 3.08 3.215 19.44 1 0 3 1
5 175 175 360.0 175 3.15 3.440 17.02 0 0 3 2
6 105 105 225.0 105 2.76 3.460 20.22 1 0 3 1
7 245 245 360.0 245 3.21 3.570 15.84 0 0 3 4
8 62 62 146.7 62 3.69 3.190 20.00 1 0 4 2
9 95 95 140.8 95 3.92 3.150 22.90 1 0 4 2
10 123 123 167.6 123 3.92 3.440 18.30 1 0 4 4
...
I'm sorry for the confusion but eventually, the first example I posted (at the bottom of the page), did not help me to figure out how tidyeval works with mutate, so I'm adding a new example.
I would like to create a function that takes three args:
- a dataframe
- the column(s) to mutate
- a variable (from the dataframe) to replace the values that are being mutated
For instance, to replace the values in mpg with the values from carb I tried this:
I tried this
colToX <- function(dt, ..., repl) {
cols <- quos(...)
repl <- quo(repl)
mutate_at(dt, vars(!!!cols), funs(function(x) !!repl))
}
colToX(mtcars, mpg, repl = carb)
which doesn't work since:
Error in mutate_impl(.data, dots) : Column
mpgis of unsupported type function
My first example (@MrFlick's and @UseR's both work fine for this):
For instance, the one below should mutate() assigning all 1 to the variable passed in ...
colTo1 <- function(dt, ...) {
col <- quo(...)
mutate(mtcars, !!col := 1)
}
colTo1(mtcars, mpg)
Error: LHS must be a name or string
Eventually, the output should be the same as mutate(mtcars, mpg = 1)
@MrFlick's solution works for the one column case, but since OP used ... as an argument, I assume OP would also want the function to be able to take in multiple columns. For example, the following would not work:
colTo1 <- function(dt, ...) {
col <- quo_name(quo(...))
mutate(dt, !!col := 1)
}
colTo1(mtcars, mpg, cyl)
Error in inherits(x, "quosure") : object 'cyl' not found
What we can do is to use quos instead of quo and mutate_at instead of mutate:
colTo1 <- function(dt, ...) {
cols <- quos(...)
mutate_at(dt, vars(!!!cols), function(x) x=1)
}
quos converts each argument from ... into vector of quosures. Using mutate_at's vars syntax and explicit splicing with !!! from rlang, we can unquote each quosure in cols, and mutate on those specified columns.
Now this works as intended:
colTo1(mtcars, mpg, cyl)
Result:
mpg cyl disp hp drat wt qsec vs am gear carb
1 1 1 160.0 110 3.90 2.620 16.46 0 1 4 4
2 1 1 160.0 110 3.90 2.875 17.02 0 1 4 4
3 1 1 108.0 93 3.85 2.320 18.61 1 1 4 1
4 1 1 258.0 110 3.08 3.215 19.44 1 0 3 1
5 1 1 360.0 175 3.15 3.440 17.02 0 0 3 2
6 1 1 225.0 105 2.76 3.460 20.22 1 0 3 1
7 1 1 360.0 245 3.21 3.570 15.84 0 0 3 4
8 1 1 146.7 62 3.69 3.190 20.00 1 0 4 2
9 1 1 140.8 95 3.92 3.150 22.90 1 0 4 2
10 1 1 167.6 123 3.92 3.440 18.30 1 0 4 4
...
It's also easy enough to let "1" be another argument to be passed into the function:
colToX <- function(dt, ..., X) {
cols <- quos(...)
mutate_at(dt, vars(!!!cols), function(x) x=X)
}
colToX(mtcars, mpg, cyl, X = 2)
Edit: OP changed the question to require that X should be another column in the same dataframe. Below is my new solution:
colToX <- function(dt, ..., X) {
cols <- quos(...)
X_quo <- enquo(X)
mutate_at(dt, vars(!!!cols), funs(.data$`!!`(X_quo)))
}
colToX(mtcars, mpg, cyl, X = hp)
Here, I am using the funs function to create a list of function calls to each column referenced from vars. .data refers to the input dataframe into mutate_at (in this case dt). I used enquo to convert what's called from X into a quosure and unquote it using !!.
Result:
mpg cyl disp hp drat wt qsec vs am gear carb
1 110 110 160.0 110 3.90 2.620 16.46 0 1 4 4
2 110 110 160.0 110 3.90 2.875 17.02 0 1 4 4
3 93 93 108.0 93 3.85 2.320 18.61 1 1 4 1
4 110 110 258.0 110 3.08 3.215 19.44 1 0 3 1
5 175 175 360.0 175 3.15 3.440 17.02 0 0 3 2
6 105 105 225.0 105 2.76 3.460 20.22 1 0 3 1
7 245 245 360.0 245 3.21 3.570 15.84 0 0 3 4
8 62 62 146.7 62 3.69 3.190 20.00 1 0 4 2
9 95 95 140.8 95 3.92 3.150 22.90 1 0 4 2
10 123 123 167.6 123 3.92 3.440 18.30 1 0 4 4
...
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