ggplot2 (version 1.0.1)

geom_line: Connect observations, ordered by x value.


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 overlapping 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.


[results=rd,stage=build]{ggplot2:::rd_aesthetics("geom", "line")} # 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)

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