scale_discrete

Position scales for discrete data and then convert them with ggplotly.

ggplot(diamonds, aes(cut)) + geom_bar()

plotly::ggplotly(p)

(d <- ggplot(subset(diamonds, carat > 1), aes(cut, clarity)) +
      geom_jitter())

plotly::ggplotly(d)

(d <- ggplot(subset(diamonds, carat > 1), aes(cut, clarity)) +
      geom_jitter())
p <-  d + scale_x_discrete("Cut")

plotly::ggplotly(p)

(d <- ggplot(subset(diamonds, carat > 1), aes(cut, clarity)) +
      geom_jitter())
p <-    
 d +
  scale_x_discrete(
    "Cut",
    labels = c(
      "Fair" = "F",
      "Good" = "G",
      "Very Good" = "VG",
      "Perfect" = "P",
      "Ideal" = "I"
    )
  )

plotly::ggplotly(p)

(d <- ggplot(subset(diamonds, carat > 1), aes(cut, clarity)) +
      geom_jitter())
p <-  d + scale_x_discrete(limits = c("Fair","Ideal"))

plotly::ggplotly(p)

(d <- ggplot(subset(diamonds, carat > 1), aes(cut, clarity)) +
      geom_jitter())
p <-  d + xlim("Fair","Ideal", "Good")

plotly::ggplotly(p)

(d <- ggplot(subset(diamonds, carat > 1), aes(cut, clarity)) +
      geom_jitter())
p <-  d + ylim("I1", "IF")

plotly::ggplotly(p)

p <-    
 ggplot(mpg, aes(manufacturer, cty)) +
  geom_point()

plotly::ggplotly(p)

p <-    
 ggplot(mpg, aes(reorder(manufacturer, cty), cty)) +
  geom_point()

plotly::ggplotly(p)

p <-    
 ggplot(mpg, aes(reorder(manufacturer, displ), cty)) +
  geom_point()

plotly::ggplotly(p)

p <-    
 ggplot(mpg, aes(reorder(manufacturer, displ), cty)) +
  geom_point() +
  scale_x_discrete(labels = abbreviate)

plotly::ggplotly(p)

GGPLOT - scale_discrete

GGPLOT - `scale_discrete`