Can't get R2 values in two decimal using ggplot2 and ggpmisc-CodePudding

I am sorry that I don't know how to make reproducible example while asking for help here. Therefore, I am providing the code below and data; <350 KB here (data:

CodePudding user response：

We can wrap the round with format and use simple paste0 to combine them. One thing to keep in mind here is the type of output from format is character.

Example:

> format(round(0.70, 2), nsmall = 2)
[1] "0.70"
> typeof(format(round(0.70, 2), nsmall = 2))
[1] "character"

Solution (only the final plot):

ggplot(data=data_all, aes(x=ta_ts, y=h, color=type))  
  geom_hline(yintercept=0, linetype="dashed", color = "grey50", size=.3)  
  geom_vline(xintercept=0, linetype="dashed", color = "grey50", size=.3)  
  geom_point(alpha=0.3, size=1.5, shape=20)  
  labs(x=NULL,
       y=expression("H"~ "[W" ~ m^-2~"]"))  
  scale_colour_manual("",values = c("Overcast"="#51806a","Clear-sky"="#DD3C51"))  
  theme_bw()  
  theme(legend.position = c(.25, .85),
        legend.background = element_rect(fill = "transparent"),
        axis.ticks.length=unit(-0.12, "cm"),
        axis.text.y = element_text(margin=margin(5,7,5,5,"pt")),
        axis.text.x = element_text(margin=margin(7,5,5,5,"pt")))  
  stat_fit_glance(method = 'lm',
                  method.args = list(formula = formula1),
                  #geom = 'text',
                  label.y = "bottom",
                  label.x = "right",
                  aes(label = paste0("R^2 =", format(round(..r.squared.., digits = 2), nsmall = 2))))

CodePudding user response：

Using stat_poly_eq() it is possible to easily adjust the number of digits. This is using the current version of 'ggpmisc' from CRAN. I updated the code recently so that trailing zeros are not dropped.

library(ggpmisc)
library(dplyr)
library(openxlsx)

# data
data_all   <- read.xlsx("./R bits and pieces/djfma_hourly_clear_overcast_scatter.xlsx")
colnames(data_all)[1] <- "h"
colnames(data_all)[2] <- "le"
colnames(data_all)[3] <- "ta_ts"
colnames(data_all)[4] <- "q_qRS"

# filter
data_clear <- data_all %>%
  filter(type == "Clear-sky")
data_over <- data_all %>%
  filter(type == "Overcast")

# Plot
ggplot(data=data_all, aes(x=ta_ts, y=h, color=type))  
  geom_hline(yintercept=0, linetype="dashed", color = "grey50", size=.3)  
  geom_vline(xintercept=0, linetype="dashed", color = "grey50", size=.3)  
  geom_point(alpha=0.3, size=1.5, shape=20)  
  labs(x=NULL,
       y=expression("H"~ "[W" ~ m^-2~"]"))  
  scale_colour_manual("",values = c("Overcast"="#51806a","Clear-sky"="#DD3C51"))  
  theme_bw()  
  theme(legend.position = c(.25, .85),
        legend.background = element_rect(fill = "transparent"),
        axis.ticks.length=unit(-0.12, "cm"),
        axis.text.y = element_text(margin=margin(5,7,5,5,"pt")),
        axis.text.x = element_text(margin=margin(7,5,5,5,"pt")))  
  stat_poly_eq(label.y = "bottom",
               label.x = "right",
               rr.digits = 2)