customizing the tooltip for ggplotly when two dataframes are used in ggplot-CodePudding

I have generated the following plot, which groups the data based on drug. I then created another data frame which summarized the main data by calculating the mean. These mean values(grouped by drug) are then added to the plot in triangular shapes. Using stat_summary connected the means. Now I would like to know how to add the tooltips for the means data (including x and y values with custom labels) to the plot using ggplotly. The current tooltip only includes the info for the main data

data:

Day,Drug,Sex,Y
1,A,Female,2.192306074
1,B,Male,4.551912798
1,B,Female,1.574070652
1,C,Female,-0.143946163
1,A,Male,5.144422967
1,C,Male,5.724705829
2,A,Male,2.691617258
2,B,Female,-3.0289955
2,C,Male,0.338102762
2,A,Female,-0.558581233
2,B,Female,-2.942620032
2,C,Male,1.024670497
3,A,Male,2.264980803
3,C,Female,2.103722883
3,A,Female,2.091621938
3,B,Male,1.535299922
3,B,Male,1.618399767
3,C,Female,0.136160703

After copying you may need to run the following command to convert it to the dataframe:

df <- read.delim("clipboard", sep = ",")

my variables are in string:

grouping_var <- "Drug"
x <- "Day"
y <- "Y"
color <- "Sex"

Here is the code for that the plot:

text <- paste("X:", df[[grouping_var]], "<br>",
              "Y:", df[[y]], "<br>",
              "group:", grouping_var, "<br>",
              "color:", color)
mean_df <- df %>% group_by(get(x), get(grouping_var)) %>% summarise(Mean = mean(get(y)), .groups = "drop") %>% 
  rename(x = 1, grouping_var = 2)

p <- df %>% ggplot(aes(x = get(x), y = get(y), text = text))  
  geom_point(aes_string(group = grouping_var, color = color))  
  stat_summary(fun=mean, geom="line", aes_string(group = grouping_var), color = "red", lty = 2)  
  geom_point(data = mean_df, aes(x = x, y = Mean, group = grouping_var, color = grouping_var),
             pch = 2, size = 3,inherit.aes = F)   

  xlab(x) 
  ylab(y)

ggplotly(p, tooltip = c("text"))

The output:

CodePudding user response：

The general approach to achieve your desired result and add a tooltip to the summary points would be to map on the text aes in your second geom_point too. However, IMHO you could simplify your code a bit and as a side effect get rid of the aes_string (which was deprecated in ggplot2 3.4.0 and should therefore be replaced by aes). To this end you could simply rename the original variables as x, y, group and color. Second, I use some small custom functions to create the tooltip texts. Finally, I replaced the stat_summary with a geom_line.

library(ggplot2)
library(plotly)

text1 <- function(x, y, group, color) {
  paste0(
    "X: ", x, "<br>",
    "Y: ", y, "<br>",
    "group (Drug): ", group, "<br>",
    "color (Sex): ", color
  )
}

text2 <- function(x, y, group, color) {
  paste0(
    "X: ", x, "<br>",
    "Y: ", y, "<br>",
    "group (Drug): ", group, "<br>"
  )
}

df <- df %>%
  rename(x = x, y = y, group = grouping_var, color = color) %>%
  mutate(text = text1(x, y, group, color))

mean_df <- df %>%
  group_by(x, group) %>%
  summarise(y = mean(y), .groups = "drop") %>%
  mutate(text = text2(x, y, group, color))

p <- df %>% ggplot(aes(
  x = x, y = y, text = text
))  
  geom_point(aes(group = group, color = color))  
  geom_line(
    data = mean_df,
    aes(group = group),
    color = "red", lty = 2
  )  
  geom_point(
    data = mean_df,
    aes(color = group, text = text),
    pch = 2, size = 3
  )  
  xlab(x)  
  ylab(y)

ggplotly(p, tooltip = c("text"))