ggally_trends | R Documentation |
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)
data |
data set using |
mapping |
aesthetics being used |
... |
other arguments passed to |
include_zero |
Should 0 be included on the y-axis? |
Joseph Larmarange
# 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
))
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