在r中的group_by之后建模后取消嵌套列表列 [英] unnest a list column after modeling after group_by in r

问题描述

我想对 group_by 之后的所有组进行线性回归，将模型系数保存在列表列中，然后使用"unnest"扩展列表列".这里我以 mtcars 数据集为例.

I want to do linear regression for all groups after group_by, save the model coefficients in a list column and then 'expand the list column' using 'unnest'. Here I use mtcars dataset as an example.

注意:我想在这里使用 do'，因为 broom :: tidy`不适用于所有型号.

Note: I want to use do' here, becausebroom::tidy` does not work for all models.

mtcars %>% group_by(cyl) %>% 
    do(model=lm(mpg~wt+hp, data=.)) %>% 
    mutate(coefs = list(summary(model)$coefficients)) %>% 
    unnest()

我想要这样的东西.

cyl   term         Estimate Std. Error   t value     Pr(>|t|)
 4     (Intercept) 36.9083305 2.19079864 16.846975 1.620660e-16
 4     wt         -2.2646936 0.57588924 -3.932516 4.803752e-04
 4     hp          -0.0191217 0.01500073 -1.274718 2.125285e-01
 6.......
 6......
........

我收到如下错误:

Error: All nested columns must have the same number of elements.

任何人都可以帮助解决此问题吗?尝试了很多次后，我无法理解它.

Can anyone help solving this issue? I could not figure it our after trying so many times...

推荐答案

一种选择是提取'coefs'列(.$ coefs )，设置列表的名称列和'cyl'列，并通过 map 遍历 list ，将其转换为 data.frame ，创建一个新列基于行名，并使用 .id 从 list

One option would be to extract the 'coefs' column (.$coefs), set the names of the list column with 'cyl' column, loop through the list with map, convert it to data.frame, create a new column based on the row names and use the .id to create the 'cyl' column from the names of the list

library(tidyverse)
mtcars %>% 
   group_by(cyl) %>% 
   do(model=lm(mpg~ wt + hp, data=.)) %>% 
   mutate(coefs = list(summary(model)$coefficients)) %>%
                 select(-model) %>% 
   {set_names(.$coefs, .$cyl)} %>%
   map_df(~ .x %>% 
               as.data.frame %>%
               rownames_to_column('term'), .id = 'cyl')
# cyl        term    Estimate Std. Error   t value     Pr(>|t|)
#1   4 (Intercept) 45.83607319 4.78693568  9.575243 1.172558e-05
#2   4          wt -5.11506233 1.60247105 -3.191984 1.276524e-02
#3   4          hp -0.09052672 0.04359827 -2.076383 7.151610e-02
#4   6 (Intercept) 32.56630096 5.57482132  5.841676 4.281411e-03
#5   6          wt -3.24294031 1.37365306 -2.360815 7.759393e-02
#6   6          hp -0.02219994 0.02017664 -1.100279 3.329754e-01
#7   8 (Intercept) 26.66393686 3.66217797  7.280896 1.580743e-05
#8   8          wt -2.17626765 0.72094143 -3.018647 1.168393e-02
#9   8          hp -0.01367295 0.01073989 -1.273099 2.292303e-01

如果我们想使用 tidy ，则将 map_df 的内容更改为

If we wanted to use tidy, then change the contents of map_df to

       ...                %>%
        map_df(~ .x %>% 
                          broom::tidy(.), .id = 'cyl')

---

此外，另一种选择是在 group_by 之后进行 nest ，然后在 model broom :: tidy >对象，然后 unnest

---

Also, another option is to nest after group_by and then apply the broom::tidy on the model object and then unnest

mtcars %>% 
   group_by(cyl) %>%
   nest %>% 
   mutate(data = map(data, ~ .x %>%
                    summarise(model = list(broom::tidy(lm(mpg ~ wt + hp)))))) %>% 
   unnest %>% 
   unnest

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