使用dplyr行绑定列表列
在为每个模型添加标识符后，我想找到一种更好的方法来将任意数量的回归结果绑定在一起。下面的代码是我当前的解决方案，但对于大量回归来说太手动了。这是一个更大的整洁工作流程的一部分，因此内部的解决方案tidyverse是首选，但任何工作都很好。谢谢
library(tidyverse)
library(broom)
model_dat=mtcars %>%
do(lm_1 = tidy(lm(disp~ wt*vs, data = .),conf.int=T),
lm_2=tidy(lm(cyl ~ wt*vs, data = .),conf.int=T ),
lm_3=tidy(lm(mpg ~ wt*vs, data = .),conf.int=T ))
df=model_dat %>%
select(lm_1) %>%
unnest(c(lm_1)) %>%
mutate(model="one") %>%
select(model,term,estimate,p.value:conf.high) %>%
bind_rows(
model_dat %>%
select(lm_2) %>%
unnest(c(lm_2)) %>%
mutate(model="two") %>%
select(model,term,estimate,p.value:conf.high)) %>%
bind_rows(
model_dat %>%
select(lm_3) %>%
unnest(c(lm_3)) %>%
mutate(model="three") %>%
select(model,term,estimate,p.value:conf.high))
回答
它可以是与更容易map2跨越列即循环和相应的english为列的序列单词pluck的list元素，创建与第二个参数即“模式”列engish字（.y），select感兴趣的列，并且通过指定建立一个单一的数据集_dfr在map
library(purrr)
library(english)
library(dplyr)
library(broom)
map2_dfr(model_dat, as.character(english(seq_along(model_dat))),
~ .x %>%
pluck(1) %>%
mutate(model = .y) %>%
select(model, term, estimate, p.value:conf.high) )
-输出
# A tibble: 12 x 6
# model term estimate p.value conf.low conf.high
# <chr> <chr> <dbl> <dbl> <dbl> <dbl>
# 1 one (Intercept) -70.0 1.55e- 1 -168. 28.2
# 2 one wt 102. 8.20e- 9 76.4 128.
# 3 one vs 31.2 6.54e- 1 -110. 172.
# 4 one wt:vs -36.7 1.10e- 1 -82.2 8.82
# 5 two (Intercept) 4.31 1.28e- 5 2.64 5.99
# 6 two wt 0.849 4.90e- 4 0.408 1.29
# 7 two vs -2.19 7.28e- 2 -4.59 0.216
# 8 two wt:vs 0.0869 8.20e- 1 -0.689 0.862
# 9 three (Intercept) 29.5 6.55e-12 24.2 34.9
#10 three wt -3.50 2.33e- 5 -4.92 -2.08
#11 three vs 11.8 4.10e- 3 4.06 19.5
#12 three wt:vs -2.91 2.36e- 2 -5.40 -0.419
或者使用summarisewith across，unclass然后绑定 withbind_rows
model_dat %>%
summarise(across(everything(), ~ {
# // get the column name
nm1 <- cur_column()
# // extract the list element (.[[1]])
list(.[[1]] %>%
# // create new column by extracting the numeric part
mutate(model = english(readr::parse_number(nm1))) %>%
# // select the subset of columns, wrap in a list
select(model, term, estimate, p.value:conf.high))
}
)) %>%
# // unclass to list
unclass %>%
# // bind the list elements
bind_rows
-输出
# A tibble: 12 x 6
# model term estimate p.value conf.low conf.high
# <english> <chr> <dbl> <dbl> <dbl> <dbl>
# 1 one (Intercept) -70.0 1.55e- 1 -168. 28.2
# 2 one wt 102. 8.20e- 9 76.4 128.
# 3 one vs 31.2 6.54e- 1 -110. 172.
# 4 one wt:vs -36.7 1.10e- 1 -82.2 8.82
# 5 two (Intercept) 4.31 1.28e- 5 2.64 5.99
# 6 two wt 0.849 4.90e- 4 0.408 1.29
# 7 two vs -2.19 7.28e- 2 -4.59 0.216
# 8 two wt:vs 0.0869 8.20e- 1 -0.689 0.862
# 9 three (Intercept) 29.5 6.55e-12 24.2 34.9
#10 three wt -3.50 2.33e- 5 -4.92 -2.08
#11 three vs 11.8 4.10e- 3 4.06 19.5
#12 three wt:vs -2.91 2.36e- 2 -5.40 -0.419