Description Usage Arguments Details Aesthetics See Also Examples
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.
1 2 3 4 5 6 7 8 9 10 11 12 | geom_path(mapping = NULL, data = NULL, stat = "identity",
position = "identity", ..., lineend = "butt", linejoin = "round",
linemitre = 10, 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, ...)
|
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
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 |
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 |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
direction |
direction of stairs: 'vh' for vertical then horizontal, or 'hv' for horizontal then vertical |
An alternative parameterisation is geom_segment()
: each line
corresponds to a single case which provides the start and end coordinates.
geom_path
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
group
linetype
size
Learn more about setting these aesthetics in vignette("ggplot2-specs")
geom_polygon()
: Filled paths (polygons);
geom_segment()
: Line segments
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | # 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 changes
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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