Creating a % calculation to use in a plot

[cupricfae]

Currently I'm using a mosaicplot to see an accuracy vs length of vowel comparison (based on if someone knows Japanese). My code is working, but is there a way that I can calculate a % value for my JAcc column using boxplot or some other categorical-friendly function?

For that matter, I get some weird results already when I try to boxplot it

Original mosaicplot code:

mosaicplot(table(JA1$JAcc, JA1$Length))

attempt at boxplot code:

ggplot(data = JA1) +
  geom_boxplot(mapping = aes(x = JAcc, y = Length))

results in:

[andresrcs]

We don't really have enough info to help you out. 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.…

[cupricfae]

this should be the information needed?

> head(JA1)
# A tibble: 6 x 9
  Participant Experiment Question Order Length Quality Response JAcc        LengthLanguage
        <dbl>      <dbl>    <dbl> <dbl> <chr>  <chr>   <chr>    <chr>       <chr>         
1           1          1        1     1 short  u       long     Noincorrect No            
2           1          1        2     2 short  i       long     Noincorrect No            
3           1          1        3     3 long   e       long     Nocorrect   No            
4           1          1        4     4 short  a       short    Nocorrect   No            
5           1          1        5     5 long   o       short    Noincorrect No            
6           1          1        6     6 long   a       long     Nocorrect   No    

library(tidyverse)
ComprrJAcc <- unite(Comprr, JAcc, Japanese, Accuracy, sep = "")
#and .     these were done as separate operations if that matters, not done together
ComprrJAcc %>% filter(Experiment=="1") -> JA1

#this is the code I ran
ggplot(ComprrJAcc) +
  geom_boxplot(aes(x=JAcc, y=Length))

#Following is the console message
> ggplot(data = JA1) +
  +   geom_boxplot(aes(x=JAcc, y=Length))

the graph is the same as above:

hopefully this is enough information to reproduce it

[drevanzyl]

You could get the % short/long length for each JAcc category. I've used simulated data which gives you an artificial 50% mean for each category. The means for your data should vary.

library(ggplot2)
JA1 <- expand.grid(Length=c("short","long"), 
            JAcc=c("Noincorrect","Nocorrect","Yescorrect","Yesincorrect"))

ggplot(JA1) +
  geom_boxplot(aes(x=JAcc, y=round(mean(Length=="long")*100, digits = 2)))

^{Created on 2019-11-22 by the reprex package (v0.3.0)}

[andresrcs]

It is not clear to me what your desired output is, you cant make a boxplot out of a categorical variable but considering your variable selection, maybe you want to do something like this?

JA1 <- data.frame(stringsAsFactors=FALSE,
                  Participant = c(1, 1, 1, 1, 1, 1),
                  Experiment = c(1, 1, 1, 1, 1, 1),
                  Question = c(1, 2, 3, 4, 5, 6),
                  Order = c(1, 2, 3, 4, 5, 6),
                  Length = c("short", "short", "long", "short", "long", "long"),
                  Quality = c("u", "i", "e", "a", "o", "a"),
                  Response = c("long", "long", "long", "short", "short", "long"),
                  JAcc = c("Noincorrect", "Noincorrect", "Nocorrect", "Nocorrect",
                           "Noincorrect", "Nocorrect"),
                  LengthLanguage = c("No", "No", "No", "No", "No", "No")
)

library(tidyverse)

JA1 %>% 
    count(Length, JAcc, name = "Prop") %>%
    group_by(JAcc) %>% 
    mutate(Prop = Prop/sum(Prop) * 100) %>% 
    ggplot(aes(x=JAcc, y = Length, fill = Prop)) +
    geom_tile() +
    geom_text(aes(label = scales::number(Prop, 
                                         accuracy = 0.1,
                                         suffix = "%")),
              color = "white") +
    scale_fill_gradient(limits = c(0, 100))

[cupricfae]

I figured out why it was failing to give me what I wanted, I was mixing up my bar and boxplot functions, but this actually works wonderfully for what i was trying to get done and works better as a visualization than what I had in mind!

[andresrcs]

@cupricfae

I was mixing up my bar and boxplot functions,

That makes much more sense actually, I think this would be more appropriate.

library(tidyverse)

JA1 %>% 
    count(Length, JAcc, name = "Prop") %>%
    group_by(JAcc) %>% 
    mutate(Prop = Prop/sum(Prop) * 100) %>% 
    ggplot(aes(x = JAcc, y = Prop, fill = Length)) +
    geom_col() +
    geom_text(aes(label = scales::number(Prop, 
                                         accuracy = 0.1,
                                         suffix = "%")),
              color = "white",
              position = "stack",
              vjust = 1.5)