遍历purrr中的公式 [英] iterating over formulas in purrr
问题描述
我想一堆使用一堆公式(例如字符串),最好一次使用tidyverse函数.这就是我现在的位置.
I have a bunch of formulas, as strings, that I'd like to use, one at a time in a glm, preferably using tidyverse functions. Here's where I am at now.
library(tidyverse)
library(broom)
mtcars %>% dplyr::select(mpg:qsec) %>% colnames -> targcols
paste('vs ~ ', targcols) -> formulas
formulas
#> 'vs ~ mpg' 'vs ~ cyl' 'vs ~ disp' 'vs ~ hp' 'vs ~ drat' 'vs ~ wt' 'vs ~ qsec'
我可以使用这些公式中的任何一个运行通用线性模型
I can run a general linear model with any one of these formulas as
glm(as.formula(formulas[1]), family = 'binomial', data = mtcars) %>% glance
#> null.deviance, df.null, logLik, AIC, BIC, deviance, df.residual
#> 43.86011, 31, -12.76667, 29.53334, 32.46481, 25.53334, 30
我想使用列表中的所有可能公式运行glm.我尝试这样做,如下.
I'd like to run the glm with every possible formula in the list. I tried doing that as follows.
data.frame(formulas = formulas) %>%
mutate(mod = map(formulas, function(fs){
glm(as.formula(fs), family = 'binomial', data = mtcars)
}))
但是随后我收到以下错误消息:
But then I get the following error message:
Error in mutate_impl(.data, dots): Evaluation error: invalid formula. Traceback:
1. data.frame(formulas = formulas) %>% mutate(mod = map(formulas, . function(fs) { . glm(as.formula(fs), family =
"binomial", data = mtcars) . }))
2. withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
3. eval(quote(`_fseq`(`_lhs`)), env, env)
4. eval(quote(`_fseq`(`_lhs`)), env, env)
5. `_fseq`(`_lhs`)
6. freduce(value, `_function_list`)
7. withVisible(function_list[[k]](value))
8. function_list[[k]](value)
9. mutate(., mod = map(formulas, function(fs) { . glm(as.formula(fs), family = "binomial", data = mtcars) . }))
10. mutate.data.frame(., mod = map(formulas, function(fs) { . glm(as.formula(fs), family = "binomial", data = mtcars) . }))
11. as.data.frame(mutate(tbl_df(.data), ...))
12. mutate(tbl_df(.data), ...)
13. mutate.tbl_df(tbl_df(.data), ...)
14. mutate_impl(.data, dots)
有人可以告诉我我在这里想念的吗?感谢您的任何建议.
Could somebody tell me what I am missing here? Thanks for any advice.
推荐答案
问题是您使用的是data.frame()
,默认情况下(stringAsFactors=TRUE
)将data.frame()
转换为公式向量.
The problem is that you're using data.frame()
, which by default (stringAsFactors=TRUE
) converts your formula vector to a factor.
将data.frame
更改为data_frame
对我有用. (data_frame
来自tibble
包,也通过dplyr
导出,因此应该在library("tidyverse")
之后可用)
Changing data.frame
to data_frame
works for me. (data_frame
is from the tibble
package, also exported via dplyr
, so it should be available after library("tidyverse")
)
您可以将代码缩短一点:
You can shorten your code a little bit:
data_frame(formulas) %>%
mutate(mod = map(formulas,
~ glm(as.formula(.),
family = 'binomial', data = mtcars)))
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