models_purrr

library(purrr)
library(tidyverse)

newdata=data.frame(Sepal.Length=seq(4, 8, by=.5))
# newdata$Sepal.Length
fitted_models <- iris %>%
  nest(data = -Species) %>% 
  mutate(fit = map(data, ~ lm(Petal.Length ~ Sepal.Length + I(Sepal.Length^2), data = .x)),
         # fitted = map(fit, "fitted.values"),
         predicted_Petal.Length= map(fit, ~ predict(.x, newdata = newdata))
         ) %>% 
  unnest(cols = c(predicted_Petal.Length)) %>% 
  select(Species, predicted_Petal.Length) %>% 
  mutate(Sepal.Length=rep(newdata$Sepal.Length, 3)) %>% 
  rename(Petal.Length= predicted_Petal.Length)  

fitted_models %>% 
  ggplot()+
  aes(Sepal.Length, Petal.Length, col=Species)+
  geom_point(data=iris, aes(Sepal.Length, Petal.Length, col=Species))+
  geom_line() + 
  geom_point(data=fitted_models %>% 
               group_by(Species) %>% 
               slice(which.max(Petal.Length)), 
             col="black") 

fitted_models %>% 
  group_by(Species) %>% 
  slice(which.max(Petal.Length))