geom_density {ggplot2} | R Documentation

## Display a smooth density estimate.

### Description

A kernel density estimate, useful for display the distribution of variables with underlying smoothness.

### Usage

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

    stat_density(mapping = NULL, data = NULL, geom = "area",
      position = "stack", ..., bw = "nrd0", adjust = 1, kernel = "gaussian",
      trim = FALSE, 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.
`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.
`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`.
`geom, stat` | Use to override the default connection between `geom_density` and `stat_density`.
`bw` | the smoothing bandwidth to be used, see `density` for details
`adjust` | adjustment of the bandwidth, see `density` for details
`kernel` | kernel used for density estimation, see `density` for details
`trim` | This parameter only matters if you are displaying multiple densities in one plot. If `FALSE`, the default, each density is computed on the full range of the data. If `TRUE`, each density is computed over the range of that group: this typically means the estimated x values will not line-up, and hence you won't be able to stack density values.

### Aesthetics

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

- `x`

- `y`

- `alpha`

- `colour`

- `fill`

- `linetype`

- `size`

- `weight`

### Computed variables

density

  density estimate

count

  density * number of points - useful for stacked density plots

scaled

  density estimate, scaled to maximum of 1

### See Also

See `geom_histogram`, `geom_freqpoly` for other methods of displaying continuous distribution. See `geom_violin` for a compact density display.

### Examples

    ggplot(diamonds, aes(carat)) +
      geom_density()

    ggplot(diamonds, aes(carat)) +
      geom_density(adjust = 1/5)
    ggplot(diamonds, aes(carat)) +
      geom_density(adjust = 5)

    ggplot(diamonds, aes(depth, colour = cut)) +
      geom_density() +
      xlim(55, 70)
    ggplot(diamonds, aes(depth, fill = cut, colour = cut)) +
      geom_density(alpha = 0.1) +
      xlim(55, 70)

    # Stacked density plots: if you want to create a stacked density plot, you
    # probably want to 'count' (density * n) variable instead of the default
    # density

    # Loses marginal densities
    ggplot(diamonds, aes(carat, fill = cut)) +
      geom_density(position = "stack")
    # Preserves marginal densities
    ggplot(diamonds, aes(carat, ..count.., fill = cut)) +
      geom_density(position = "stack")

    # You can use position="fill" to produce a conditional density estimate
    ggplot(diamonds, aes(carat, ..count.., fill = cut)) +
      geom_density(position = "fill")

[Package ggplot2 version 2.1.0 Index]