ZeroStack ZeroStack - 1 month ago 23
R Question

R plotly version 4.5.2 scatterplot legend bubble size settings

I am using plotly 4.5.2 in R. I have created a scatterplot which is sized on a variable, the issue is these sizes are also reflected in the legend which makes them hard to read.

I want my graph to remain the same, with the only exception being the size of the bubbles in the legend. These bubbles can either be set to all be the same size or scaled to a smaller size. Importantly, the sizes in the graph must remain the same.

enter image description here

Please find reproducible code here:

library(plotly)

data <- data.frame(name = c('test1', 'test2', 'test3', 'test4'),
x = c(1, 15, 90, 45),
y = c(9, 43, 43, 53),
size = c(10000, 50000, 90000, 3000),
colour = c("rgba(230, 42, 56, 0.3)", "rgba(76, 175, 80, 0.3)",
"rgba(32, 169, 242, 0.3)", "rgba(255, 193, 7, 0.3)")
)

plot <- plot_ly(data = data) %>%
add_trace(x = ~x,
y = ~y,
mode = 'markers',
type = 'scatter',
color = ~name,
marker = list(
color = ~colour,
opacity = 1,
showlegend=T),
size = ~size)


Thank you

Answer

I found a hack to get the desired output, i'm posting it here for the benefit of others.

library(plotly)

data <- data.frame(name = c('test1', 'test2', 'test3', 'test4'),
                      x = c(1, 15, 90, 45),
                      y = c(9, 43, 43, 53),
                      size = c(10000, 50000, 90000, 3000),
                      colour = c("rgba(230, 42, 56, 0.3)", "rgba(76, 175, 80, 0.3)",
                                 "rgba(32, 169, 242, 0.3)", "rgba(255, 193, 7, 0.3)")
                      )


#Ranges
xmin <- - 0.2 * max(data[['x']])
xmax <- 1.8 * max(data[['x']])
ymin <- - 0.2 * max(data[['y']])
ymax <- 1.8 * max(data[['y']])


# Sum of the size variable
sum_size <- sum(data[['size']], na.rm = TRUE)

# Decimal size
data$size <- (data[['size']]/sum_size)

# Adjust for the smallest 
data <- data %>% mutate(size = ifelse(size < 0.05, 0.05, size))

#Size Vector
size <- data$size * 100

# not used atm
min_size <- min(data$size, na.rm = TRUE)
max_size <- max(data$size, na.rm = TRUE)


# Number of unique groups
num_bubbles <- length(unique(data[['name']])) 


# Artifical data used to resolve legend sizes
data2 <- data
data2$size <- min_size
data2[['x']] <- -2 * max(-xmin,-ymin)
data2[['y']] <- -2 * max(-xmin,-ymin)

# Bind the artifial data, plotly will only plot the original and this fixes the legend size issue
data <- rbind(data, data2)

plot <- plot_ly(data = data) %>% 
  add_trace(x = data[['x']],
            y = data[['y']],
            mode = 'markers',
            type = 'scatter',
            color = data[['name']], 
            marker = list(size = 10,
                          opacity = 1,sizemin=10,sizemax =100,sizeref = 100,
                          line = list(width = 2)),size = 30,showlegend=T,
            hoverinfo = "text") %>% 
  add_trace( x = -2 * max(-xmin,-ymin) , y = -2 * max(-xmin,-ymin), type = "scatter", mode = "markers", 
             color= data[['name']], showlegend=F) %>% config(modeBarButtonsToRemove = list("sendDataToCloud","pan2d","select2d","lasso2d","zoomIn2d","zoomOut2d","autoScale2d","resetScale2d","hoverClosestCartesian","hoverCompareCartesian"), displaylogo = FALSE, doubleClick = "reset")  



plot <- layout(plot,
               title = NULL,

               xaxis = list(           

                 title = 'x',
                 range = c(xmin,xmax),
                 showgrid = F     
               ),
               yaxis = list(         
                 title = 'y',

                 range = c(ymin,ymax)
               ))

plot <- plotly_build(plot)

for(i in seq(1,num_bubbles))
{
  plot$x$data[[i]]$marker$size <- c(size[i]*10000,min(size)*10000)


}

enter image description here

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