Connect observations

geom_path() connects the observations in the order in which they appear in the data. geom_line() connects them in order of the variable on the x axis. geom_step() creates a stairstep plot, highlighting exactly when changes occur. The group aesthetic determines which cases are connected together.

geom_path(mapping = NULL, data = NULL, stat = "identity",
  position = "identity", ..., lineend = "butt", linejoin = "round",
  linemitre = 1, arrow = NULL, na.rm = FALSE, show.legend = NA,
  inherit.aes = TRUE)

geom_line(mapping = NULL, data = NULL, stat = "identity",
  position = "identity", na.rm = FALSE, show.legend = NA,
  inherit.aes = TRUE, ...)

geom_step(mapping = NULL, data = NULL, stat = "identity",
  position = "identity", direction = "hv", na.rm = FALSE,
  show.legend = NA, inherit.aes = TRUE, ...)

Arguments

mapping	Set of aesthetic mappings created by aes or aes_. If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.
data	The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot. A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify for which variables will be created. A function will be called with a single argument, the plot data. The return value must be a data.frame., and will be used as the layer data.
stat	The statistical transformation to use on the data for this layer, as a string.
position	Position adjustment, either as a string, or the result of a call to a position adjustment function.
...	other arguments passed on to layer. These are often aesthetics, used to set an aesthetic to a fixed value, like color = "red" or size = 3. They may also be parameters to the paired geom/stat.
lineend	Line end style (round, butt, square)
linejoin	Line join style (round, mitre, bevel)
linemitre	Line mitre limit (number greater than 1)
arrow	Arrow specification, as created by arrow
na.rm	If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.
show.legend	logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.
inherit.aes	If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders.
direction	direction of stairs: 'vh' for vertical then horizontal, or 'hv' for horizontal then vertical

Details

An alternative parameterisation is geom_segment: each line corresponds to a single case which provides the start and end coordinates.

Aesthetics

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

• x

• y

• alpha

• colour

• group

• linetype

• size

See also

geom_polygon: Filled paths (polygons); geom_segment: Line segments

Examples

# geom_line() is suitable for time series
ggplot(economics, aes(date, unemploy)) + geom_line()
ggplot(economics_long, aes(date, value01, colour = variable)) +
  geom_line()

# geom_step() is useful when you want to highlight exactly when
# the y value chanes
recent <- economics[economics$date > as.Date("2013-01-01"), ]
ggplot(recent, aes(date, unemploy)) + geom_line()
ggplot(recent, aes(date, unemploy)) + geom_step()

# geom_path lets you explore how two variables are related over time,
# e.g. unemployment and personal savings rate
m <- ggplot(economics, aes(unemploy/pop, psavert))
m + geom_path()
m + geom_path(aes(colour = as.numeric(date)))

# Changing parameters ----------------------------------------------
ggplot(economics, aes(date, unemploy)) +
  geom_line(colour = "red")

# Use the arrow parameter to add an arrow to the line
# See ?arrow for more details
c <- ggplot(economics, aes(x = date, y = pop))
c + geom_line(arrow = arrow())
c + geom_line(
  arrow = arrow(angle = 15, ends = "both", type = "closed")
)

# Control line join parameters
df <- data.frame(x = 1:3, y = c(4, 1, 9))
base <- ggplot(df, aes(x, y))
base + geom_path(size = 10)
base + geom_path(size = 10, lineend = "round")
base + geom_path(size = 10, linejoin = "mitre", lineend = "butt")

# NAs break the line. Use na.rm = T to suppress the warning message
df <- data.frame(
  x = 1:5,
  y1 = c(1, 2, 3, 4, NA),
  y2 = c(NA, 2, 3, 4, 5),
  y3 = c(1, 2, NA, 4, 5)
)
ggplot(df, aes(x, y1)) + geom_point() + geom_line()
#> Warning: Removed 1 rows containing missing values (geom_point).
#> Warning: Removed 1 rows containing missing values (geom_path).
ggplot(df, aes(x, y2)) + geom_point() + geom_line()
#> Warning: Removed 1 rows containing missing values (geom_point).
#> Warning: Removed 1 rows containing missing values (geom_path).
ggplot(df, aes(x, y3)) + geom_point() + geom_line()
#> Warning: Removed 1 rows containing missing values (geom_point).


# Setting line type vs colour/size
# Line type needs to be applied to a line as a whole, so it can
# not be used with colour or size that vary across a line
x <- seq(0.01, .99, length.out = 100)
df <- data.frame(
  x = rep(x, 2),
  y = c(qlogis(x), 2 * qlogis(x)),
  group = rep(c("a","b"),
  each = 100)
)
p <- ggplot(df, aes(x=x, y=y, group=group))
# These work
p + geom_line(linetype = 2)
p + geom_line(aes(colour = group), linetype = 2)
p + geom_line(aes(colour = x))
# But this doesn't
should_stop(p + geom_line(aes(colour = x), linetype=2))