CODEWITHSUNDEEP
rplotggplot2scale
zephel
zephel

Reputation: 185

changing y scale when using fun.y ggplot

This an example of my data

library(ggplot)
set.seed(1)
df <- data.frame(Groups = factor(rep(1:10, each = 10)))
x <- sample(1:100, 50)
df[x, "Style"] <- "Lame"
df[-x, "Style"] <- "Cool"
df$Style <- factor(df$Style)

p <- ggplot() + stat_summary(data = df, aes(Groups, Style, fill = Style),
geom = "bar", fun.y = length, position=position_dodge())

(Sorry, this is my first question... I don't know how to present code snippets like head(df) or the actual plot in SO. Please run this code to understand my question.)

So the plot adequately presents the count of every 'Style' per 'Groups'. However, the y axis scale shows the levels of the factor variable 'Style'. Although values I am plotting are originally discrete, the count of every 'Cool' and 'Lame' per 'Groups' is continuous.

How do I change the 'y' scale of my barplot from discrete to continuous in ggplot2, in order to correspond to the count values and not the original factor levels???

Upvotes: 0

Views: 520

Answers (1)

Rorschach
Rorschach

Reputation: 32426

You can take advantage of ggplot grouping and the histogram to do this for you

p <- ggplot(df, aes(Groups, fill=Style)) + geom_histogram(position=position_dodge())

Upvotes: 2

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