Plotly and ggplot with facet_grid in R: How to to get yaxis labels to use ticktext value instead of range value?

Question

I would like to use ggplot2 facets with plotly but am running into issues with the y-axis labels showing the yaxis range values instead of the ticktext. Is there something I

Answer 1

This looks like some weird artifact from the ggplot to Plotly conversion. Anyways, all what you need to do is to add an empty string to ticktext and expand tickvals by 1.

for (i in 2:22) {
  tick_l <- length(p[['x']][['layout']][[paste('yaxis', i, sep='')]][['ticktext']]) + 1
  p[['x']][['layout']][[paste('yaxis', i, sep='')]][['tickvals']] <- seq(1, tick_l)
  p[['x']][['layout']][[paste('yaxis', i, sep='')]][['ticktext']][[tick_l]] <- ''
}

The first yaxis layout is identical to the rest but does not need fixing since it already already correctly shown.

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Fixing the whole plot needs some more tweaking. I tried to make as generic as possible but probably the conversion will break something different for each plot.

library(plotly)
library(ggplot2)
library(data.table)
library(datasets)    

#add fake model for use in facet
dt<-data.table(mtcars)
dt[,car.id:=rownames(mtcars)]
dt[,model:=substr(car.id,1,regexpr(" ",car.id)-1)][model=="",model:=car.id]

#Optional toggle: pick a few models and issue seems to go away 
#Use data=dt[model %in% c("Mazda","Merc","Toyota","Honda","Hornet")]
ggplot.test<-ggplot(dt,aes(mpg,car.id))+geom_point()+facet_grid(model~.,scales="free_y",space="free",drop=TRUE)

p <- ggplotly(ggplot.test)
len <- length(unique(dt$model))

total <- 1
for (i in 2:len) {
  total <- total + length(p[['x']][['layout']][[paste('yaxis', i, sep='')]][['ticktext']])
}

spacer <- 0.01 #space between the horizontal plots
total_length = total + len * spacer
end <- 1
start <- 1

for (i in c('', seq(2, len))) {
  tick_l <- length(p[['x']][['layout']][[paste('yaxis', i, sep='')]][['ticktext']]) + 1

  #fix the y-axis
  p[['x']][['layout']][[paste('yaxis', i, sep='')]][['tickvals']] <- seq(1, tick_l)
  p[['x']][['layout']][[paste('yaxis', i, sep='')]][['ticktext']][[tick_l]] <- ''

  end <- start - spacer
  start <- start - (tick_l - 1) / total_length
  v <- c(start, end)
  #fix the size
  p[['x']][['layout']][[paste('yaxis', i, sep='')]]$domain <- v
}

#fix the first entry which has a different name than the rest
p[['x']][['layout']][['annotations']][[3]][['y']] <- (p[['x']][['layout']][['yaxis']]$domain[2] + p[['x']][['layout']][['yaxis']]$domain[1]) /2
p[['x']][['layout']][['shapes']][[2]][['y0']] <- p[['x']][['layout']][['yaxis']]$domain[1]
p[['x']][['layout']][['shapes']][[2]][['y1']] <- p[['x']][['layout']][['yaxis']]$domain[2]

#fix the annotations
for (i in 3:len + 1) {
  #fix the y position
  p[['x']][['layout']][['annotations']][[i]][['y']] <- (p[['x']][['layout']][[paste('yaxis', i - 2, sep='')]]$domain[1] + p[['x']][['layout']][[paste('yaxis', i - 2, sep='')]]$domain[2]) /2
  #trim the text
  p[['x']][['layout']][['annotations']][[i]][['text']] <- substr(p[['x']][['layout']][['annotations']][[i]][['text']], 1, length(p[['x']][['layout']][[paste('yaxis', i - 2, sep='')]][['ticktext']]) * 3 - 3)
}

#fix the rectangle shapes in the background
for (i in seq(0,(len - 2) * 2, 2)) {
  p[['x']][['layout']][['shapes']][[i+4]][['y0']] <- p[['x']][['layout']][[paste('yaxis', i /2 + 2, sep='')]]$domain[1]
  p[['x']][['layout']][['shapes']][[i+4]][['y1']] <- p[['x']][['layout']][[paste('yaxis', i /2 + 2, sep='')]]$domain[2]
}
p

Answer 2

I have similiar issues with the ggplot to plotly conversion but came up with a different solution. Still not perfect, but with some tuning I am sure you can achieve very good results:

#Using your original dt dataframe

dt<-data.table(mtcars)
dt[,car.id:=rownames(mtcars)]
dt[,model:=substr(car.id,1,regexpr(" ",car.id)-1)][model=="",model:=car.id]



#define plot xaxis limits (+/- 10%)

limits <- dt %>%
  summarise(max = ceiling(max(mpg*1.1)),
            min = floor(min(mpg*0.9)))


#define height of subplots by finding the number of cars in each "facet"

plot_height<- dt %>%
  group_by(model) %>%
  count() %>%
  ungroup() %>%
  mutate(height_pct = n/sum(n))


#define a list of ggplots and feed it in the subplot function with the calculated limits

dt %>%
  split(.$model) %>%
  map(function(x) {
    ggplot(data=x,aes(mpg,car.id)) + geom_point()+
      facet_grid(model~.) + xlim(c(limits$min,limits$max))
  }) %>%
  subplot(margin = 0.005, shareX = T,heights = plot_height$height_pct,nrows = nrow(plot_height))