
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, ...)
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.
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.arrow
FALSE
, the default, missing values are removed with
a warning. If TRUE
, missing values are silently removed.NA
, the default, includes if any aesthetics are mapped.
FALSE
never includes, and TRUE
always includes.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
.geom_segment
: each line
corresponds to a single case which provides the start and end coordinates.
geom_polygon
: Filled paths (polygons);
geom_segment
: Line segments
# 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()
ggplot(df, aes(x, y2)) + geom_point() + geom_line()
ggplot(df, aes(x, y3)) + geom_point() + geom_line()
# 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))
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