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.

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, package = "reshape") 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 ))