lims

Modify axis, legend, and plot labels and then convert them with ggplotly

p <-    
 ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  xlim(15, 20)

plotly::ggplotly(p)

p <-    
 ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  xlim(20, 15)

plotly::ggplotly(p)

p <-    
 ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  xlim(NA, 20)

plotly::ggplotly(p)

small <- subset(mtcars, cyl == 4)
big <- subset(mtcars, cyl > 4)
p <-    
 ggplot(small, aes(mpg, wt, colour = factor(cyl))) +
  geom_point() +
  lims(colour = c("4", "6", "8"))

plotly::ggplotly(p)

small <- subset(mtcars, cyl == 4)
big <- subset(mtcars, cyl > 4)
p <-    
 ggplot(big, aes(mpg, wt, colour = factor(cyl))) +
  geom_point() +
  lims(colour = c("4", "6", "8"))

plotly::ggplotly(p)

last_month <- Sys.Date() - 0:59
df <- data.frame(
  date = last_month,
  price = c(rnorm(30, mean = 15), runif(30) + 0.2 * (1:30))
)
p <- ggplot(df, aes(date, price)) +
  geom_line() +
  stat_smooth()

plotly::ggplotly(p)

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'

last_month <- Sys.Date() - 0:59
df <- data.frame(
  date = last_month,
  price = c(rnorm(30, mean = 15), runif(30) + 0.2 * (1:30))
)
p <- ggplot(df, aes(date, price)) +
  geom_line() +
  stat_smooth()
p <-  p + lims(x= c(Sys.Date() - 30, NA), y = c(10, 20))

plotly::ggplotly(p)

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'

## Warning: Removed 30 rows containing non-finite values (stat_smooth).

last_month <- Sys.Date() - 0:59
df <- data.frame(
  date = last_month,
  price = c(rnorm(30, mean = 15), runif(30) + 0.2 * (1:30))
)
p <- ggplot(df, aes(date, price)) +
  geom_line() +
  stat_smooth()
p <-  p + coord_cartesian(xlim =c(Sys.Date() - 30, NA), ylim = c(10, 20))

plotly::ggplotly(p)

## `geom_smooth()` using method = 'loess' and formula 'y ~ x'

GGPLOT - lims

GGPLOT - `lims`