ggplot2 query - facet wrapping, removal of legends and general formatting

[wgrigg]

Hi there,

I'm new to R and just need a little push in the right direction.

My code is as follows:

crickets_tidy <- 
  tidyr::gather(Weights, 
                key = stage, 
                value = time, 
                Antennate, Stridulate, Mount)

ggplot(crickets_tidy,
       aes(x = Mass, 
           y = as.numeric(time)) +
  geom_point(size = 3,
             alpha = 1/2,
             aes(colour= stage)) +
  scale_y_continuous(breaks=seq(0, 650, 100)) +
  labs( x = "Mass of female cricket(g)",
        y = "Duration of stage (s)") +
  facet_wrap(~stage,
             labeller = as_labeller(c(
               Antennate = "Antennation",
            Stridulate = "Stridulation",
              Mount = "Mounting"))) +
  theme_minimal(base_size = 15) 


crickets_tidier <- group_by(crickets_tidy, time,stage) %>% 
  summarise(meanmass = mean(Mass,na.rm = TRUE))

This comes out with this: https://imgur.com/a/sBqjBsY

Three queries here:

• How do I swap the position of the Mounting and Stridulation sections? (So, L->R, Antennation, Stridulation, Mounting)

• How do I remove the legend to the right detailing the colours?

• Is there a way to make the three 'columns' more distinct from each other? Maybe seperated by thicker lines?

Many thanks!

[andresrcs]

It would be easier to help you out if you provide some sample data on a copy/paste friendly format. Could you ask this with a minimal REPRoducible EXample (reprex)? A reprex makes it much easier for others to understand your issue and figure out how to help.

If you've never heard of a reprex before, you might want to start by reading this FAQ:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[joels]

The code below demonstrates ways to do what you asked, using the built-in iris data frame for illustration. Inline comments explain what the next line of code is doing

library(tidyverse)

iris %>% 
  # Categorical variables are ordered alphabetically by default.
  # To reorder categorical variables, convert them to factor class and set 
  #  order using the levels argument.
  mutate(Species = factor(Species, levels=c("versicolor", "virginica", "setosa"))) %>% 
  ggplot(aes(Petal.Width, Sepal.Width, colour=Species)) +
    geom_point() +
    facet_wrap(~ Species) +
    theme_minimal(base_size = 15) + 
    # Add a border around each facet
    theme(panel.border=element_rect(fill=NA, colour="grey40")) + 
    # Don't include a legend
    guides(colour=FALSE) 

[wgrigg]

Great, thank you both. All sorted!