Connect observations, ordered by x value.


geom_line(mapping = NULL, data = NULL, stat = "identity", position = "identity",


The aesthetic mapping, usually constructed with aes or aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.
A layer specific dataset - only needed if you want to override the plot defaults.
The statistical transformation to use on the data for this layer.
The position adjustment to use for overlappling points on this layer
other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for more details.


Connect observations, ordered by x value.


geom_line understands the following aesthetics (required aesthetics are in bold):

  • x
  • y
  • alpha
  • colour
  • linetype
  • size


# Summarise number of movie ratings by year of movie mry <-, by(movies, round(movies$rating), function(df) { nums <- tapply(df$length, df$year, length) data.frame(rating=round(df$rating[1]), year = as.numeric(names(nums)), number=as.vector(nums)) })) p <- ggplot(mry, aes(x=year, y=number, group=rating)) p + geom_line()

# Add aesthetic mappings p + geom_line(aes(size = rating))

p + geom_line(aes(colour = rating))

# Change scale p + geom_line(aes(colour = rating)) + scale_colour_gradient(low="red")

p + geom_line(aes(size = rating)) + scale_size(range = c(0.1, 3))

# Set aesthetics to fixed value p + geom_line(colour = "red", size = 1)

# Use qplot instead qplot(year, number, data=mry, group=rating, geom="line")

# Using a time series qplot(date, pop, data=economics, geom="line")

qplot(date, pop, data=economics, geom="line", log="y")

qplot(date, pop, data=subset(economics, date > as.Date("2006-1-1")), geom="line")

qplot(date, pop, data=economics, size=unemploy/pop, geom="line")

# Use the arrow parameter to add an arrow to the line # See ?grid::arrow for more details c <- ggplot(economics, aes(x = date, y = pop)) # Arrow defaults to "last" library(grid) c + geom_line(arrow = arrow())

c + geom_line(arrow = arrow(angle = 15, ends = "both", type = "closed"))

# See scale_date for examples of plotting multiple times series on # a single graph # A simple pcp example y2005 <- runif(300, 20, 120) y2010 <- y2005 * runif(300, -1.05, 1.5) group <- rep(LETTERS[1:3], each = 100) df <- data.frame(id = seq_along(group), group, y2005, y2010) library(reshape2) # for melt dfm <- melt(df, id.var = c("id", "group")) ggplot(dfm, aes(variable, value, group = id, colour = group)) + geom_path(alpha = 0.5)

See also

geom_path: connect observations in data order, geom_segment: draw line segments, geom_ribbon: fill between line and x-axis