ggplot2: add regression equations and R2 and adjust their positions on plot

Question

Using df and the code below

library(dplyr) 
library(ggplot2)
library(devtools)

df <- diamonds %>%
  dplyr::filter(cut%in%c("Fair","Ideal")) %>%
  dplyr::filter(clarity%in%c("I1" ,  "SI2" , "SI1" , "VS2" , "VS1",  "VVS2")) %>%
  dplyr::mutate(new_price = ifelse(cut == "Fair", 
                                   price* 0.5, 
                                   price * 1.1))

ggplot(df, aes(x= new_price, y= carat, color = cut))+
  geom_point(alpha = 0.3)+
  facet_wrap(~clarity, scales = "free_y")+
  geom_smooth(method = "lm", se = F)

I got this plot

Thanks to @kdauria's answer to this question, I added regression equations and R2 to the plot as below

source_gist("524eade46135f6348140")
ggplot(df, aes(x= new_price, y= carat, color = cut))+
  stat_smooth_func(geom="text",method="lm",hjust=0,parse=TRUE)+
  geom_point(alpha = 0.3)+
  facet_wrap(~clarity, scales = "free_y")+
  geom_smooth(method = "lm", se = F)

Now, I want to adjust the position of the regression equations and R2 to be at a specific place in each of the facets (for example at the bottom right in each facet "e.g. 0.2 y and 0.8 x).

I tried to adjust the position through vjust and hjust but it didn't work.

Any suggestions would be highly appreciated.

Solution

Try stat_poly_eq from package ggpmisc:

library(ggpmisc)
formula <- y ~ x
ggplot(df, aes(x= new_price, y= carat, color = cut)) +
  geom_point(alpha = 0.3) +
  facet_wrap(~clarity, scales = "free_y") +
  geom_smooth(method = "lm", formula = formula, se = F) +
  stat_poly_eq(aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~")), 
               label.x.npc = "right", label.y.npc = 0.15,
               formula = formula, parse = TRUE, size = 3)

returns

See ?stat_poly_eq for other options to control the output.

Comments

[Uwe]

Please, see the answer to ggplot2: Adding Regression Line Equation and R2 on graph by the author of the ggpmisc package for more details or contact the author.