```
#Reprex Example
library(tidyverse)
library(broom)
# I do a groupwise regression
res1<- mtcars %>% group_by(cyl) %>% group_modify(.f= ~tidy(lm(mpg~disp,data = .x)))
# I try to get the results in a wider form
res2<- res1 %>% pivot_wider(names_from = c(cyl),names_repair = "minimal",
values_from = c("estimate","p.value"),-c(std.error,statistic))
res2
#> # A tibble: 2 x 7
#> term estimate_4 estimate_6 estimate_8 p.value_4 p.value_6 p.value_8
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept) 40.9 19.1 22.0 0.00000120 0.00124 0.0000259
#> 2 disp -0.135 0.00361 -0.0196 0.00278 0.826 0.0568
```

Created on 2021-04-17 by the reprex package (v2.0.0)

My issue is I want the estimate term and p value term to be together

Intent is unclear; here's one possibility

```
suppressPackageStartupMessages({
library(broom)
library(dplyr)
library(tidyr)
})
res1 <- mtcars %>%
group_by(cyl) %>%
group_modify(.f = ~ tidy(lm(mpg ~ disp, data = .x)))
res2 <- res1 %>% pivot_wider(
names_from = c(cyl), names_repair = "minimal",
values_from = c("estimate", "p.value"), -c(std.error, statistic)
)
res2 %>%
filter(term == "disp") %>%
select(estimate_4,p.value_4,estimate_6,p.value_6,estimate_8,p.value_8)
#> # A tibble: 1 x 6
#> estimate_4 p.value_4 estimate_6 p.value_6 estimate_8 p.value_8
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 -0.135 0.00278 0.00361 0.826 -0.0196 0.0568
```

The intend is to keep the estimate and p value always together of different "cyl" types. I knew the select command but that is okay if we have smaller number of columns.

relocate() from {dplyr} will change the position of columns

I understand. But can this be automated? Like if I have say, 4 categories of cyl (based on above example), I would need to do relocate or filter again. Can we write a function that always prints the estimate and p value of a particular category together?

system
Closed
May 8, 2021, 3:04pm
6
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