Create a subset of groups with mutate deplyr calculate R2

I have a dataset df. I would like to make two groups, containing a= Special and b=Up+ Down+ Left. Then I would like to have 2x determination coefficient and 2 regression lines for each subgroup in one plot. Problem is how to call these created subsets and not overplot my R2. With this code, I make a line for each single group.

library(tidyverse)

set.seed(2013)
Place <- sample(c("Up", "Down", "Left", "Special"), 100, replace = TRUE)
Value <- sample(200:1500, 100, replace = TRUE)
Conc <- sample(1:25, 100, replace = TRUE)

df <- tibble(Place, Value, Conc)

#make subgroup only Special
a <- df |> 
  filter(Place == "Special")

#make subgroup Up+Down+Left
U <-"Up"
D <-"Down"
L <-"Left"
Subgroup <- c(U,D,L)

b <- df |> 
  filter(Place %in% Subgroup)

#Scatter and Regression for all Place seperated
df |> 
  ggplot(aes(Value, Conc))+
  geom_point(aes(col = Place))+
  stat_poly_line(aes(col = Place), se = FALSE)+
  stat_poly_eq()

You haven't specified a grouping variable for the stat_poly_eq layer. In the geom_point layer and stat_poly_line layer, you have mapped the "colour" aesthetic to the Place column, but you haven't done this for stat_poly_eq, so a single R² value is produced. You can specify the group using a simple ifelse to get groups "a" and "b".

df |> 
  ggplot(aes(Value, Conc, colour = Place)) +
  geom_point() +
  stat_poly_line(se = FALSE) +
  stat_poly_eq(aes(group = ifelse(Place == "Special", "group~a", "group~b"), 
                   blah = ifelse(Place == "Special", "group~a", "group~b"),
                   label = paste0(after_stat(blah), ": ", 
                                  after_stat(rr.label))), 
               colour = "black") +
  theme_bw()