geom_path {ggplot2} | R Documentation

## Connect observations.

### Description

`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.

### Usage

    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), removes missing values with a warning. If `TRUE` silently removes missing values.
`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

### Aesthetics

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

- `x`

- `y`

- `alpha`

- `colour`

- `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()
    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))

[Package ggplot2 version 2.1.0 Index]