GGally (version 2.2.1)

ggally_trends: Trends line plot

Description

Plot trends using line plots. For continuous y variables, plot the evolution of the mean. For binary y variables, plot the evolution of the proportion.

Usage

ggally_trends(data, mapping, ..., include_zero = FALSE)

Arguments

data

data set using

mapping

aesthetics being used

...

other arguments passed to ggplot2::geom_line()

include_zero

Should 0 be included on the y-axis?

Author

Joseph Larmarange

Examples

# Small function to display plots only if it's interactive
p_ <- GGally::print_if_interactive

data(tips)
tips_f <- tips
tips_f$day <- factor(tips$day, c("Thur", "Fri", "Sat", "Sun"))

# Numeric variable
p_(ggally_trends(tips_f, mapping = aes(x = day, y = total_bill)))
p_(ggally_trends(tips_f, mapping = aes(x = day, y = total_bill, colour = time)))

# Binary variable
p_(ggally_trends(tips_f, mapping = aes(x = day, y = smoker)))
p_(ggally_trends(tips_f, mapping = aes(x = day, y = smoker, colour = sex)))

# Discrete variable with 3 or more categories
p_(ggally_trends(tips_f, mapping = aes(x = smoker, y = day)))
p_(ggally_trends(tips_f, mapping = aes(x = smoker, y = day, color = sex)))

# Include zero on Y axis
p_(ggally_trends(tips_f, mapping = aes(x = day, y = total_bill), include_zero = TRUE))
p_(ggally_trends(tips_f, mapping = aes(x = day, y = smoker), include_zero = TRUE))

# Change line size
p_(ggally_trends(tips_f, mapping = aes(x = day, y = smoker, colour = sex), size = 3))

# Define weights with the appropriate aesthetic
d <- as.data.frame(Titanic)
p_(ggally_trends(
  d,
  mapping = aes(x = Class, y = Survived, weight = Freq, color = Sex),
  include_zero = TRUE
))