geom_boxplot {ggplot2} | R Documentation

## Box and whiskers plot.

### Description

The lower and upper "hinges" correspond to the first and third quartiles (the 25th and 75th percentiles). This differs slightly from the method used by the `boxplot` function, and may be apparent with small samples. See `boxplot.stats` for for more information on how hinge positions are calculated for `boxplot`.

### Usage

    geom_boxplot(mapping = NULL, data = NULL, stat = "boxplot",
      position = "dodge", ..., outlier.colour = NULL, outlier.color = NULL,
      outlier.shape = 19, outlier.size = 1.5, outlier.stroke = 0.5,
      notch = FALSE, notchwidth = 0.5, varwidth = FALSE, na.rm = FALSE,
      show.legend = NA, inherit.aes = TRUE)

    stat_boxplot(mapping = NULL, data = NULL, geom = "boxplot",
      position = "dodge", ..., coef = 1.5, 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.
`outlier.colour, outlier.color, outlier.shape, outlier.size, outlier.stroke` | Default aesthetics for outliers. Set to `NULL` to inherit from the aesthetics used for the box. In the unlikely event you specify both US and UK spellings of colour, the US spelling will take precedence.
`notch` | if `FALSE` (default) make a standard box plot. If `TRUE`, make a notched box plot. Notches are used to compare groups; if the notches of two boxes do not overlap, this suggests that the medians are significantly different.
`notchwidth` | for a notched box plot, width of the notch relative to the body (default 0.5)
`varwidth` | if `FALSE` (default) make a standard box plot. If `TRUE`, boxes are drawn with widths proportional to the square-roots of the number of observations in the groups (possibly weighted, using the `weight` aesthetic).
`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_boxplot` and `stat_boxplot`.
`coef` | length of the whiskers as multiple of IQR. Defaults to 1.5

### Details

The upper whisker extends from the hinge to the highest value that is within 1.5 * IQR of the hinge, where IQR is the inter-quartile range, or distance between the first and third quartiles. The lower whisker extends from the hinge to the lowest value within 1.5 * IQR of the hinge. Data beyond the end of the whiskers are outliers and plotted as points (as specified by Tukey).

In a notched box plot, the notches extend `1.58 * IQR / sqrt(n)`. This gives a roughly 95 See McGill et al. (1978) for more details.

### Aesthetics

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

- `lower`

- `middle`

- `upper`

- `x`

- `ymax`

- `ymin`

- `alpha`

- `colour`

- `fill`

- `linetype`

- `shape`

- `size`

- `weight`

### Computed variables

width

  width of boxplot

ymin

  lower whisker = smallest observation greater than or equal to lower hinge - 1.5 * IQR

lower

  lower hinge, 25% quantile

notchlower

  lower edge of notch = median - 1.58 * IQR / sqrt(n)

middle

  median, 50% quantile

notchupper

  upper edge of notch = median + 1.58 * IQR / sqrt(n)

upper

  upper hinge, 75% quantile

ymax

  upper whisker = largest observation less than or equal to upper hinge + 1.5 * IQR

### References

McGill, R., Tukey, J. W. and Larsen, W. A. (1978) Variations of box plots. The American Statistician 32, 12-16.

### See Also

`stat_quantile` to view quantiles conditioned on a continuous variable, `geom_jitter` for another way to look at conditional distributions.

### Examples

    p <- ggplot(mpg, aes(class, hwy))
    p + geom_boxplot()
    p + geom_boxplot() + geom_jitter(width = 0.2)
    p + geom_boxplot() + coord_flip()

    p + geom_boxplot(notch = TRUE)
    p + geom_boxplot(varwidth = TRUE)
    p + geom_boxplot(fill = "white", colour = "#3366FF")
    # By default, outlier points match the colour of the box. Use
    # outlier.colour to override
    p + geom_boxplot(outlier.colour = "red", outlier.shape = 1)

    # Boxplots are automatically dodged when any aesthetic is a factor
    p + geom_boxplot(aes(colour = drv))

    # You can also use boxplots with continuous x, as long as you supply
    # a grouping variable. cut_width is particularly useful
    ggplot(diamonds, aes(carat, price)) +
      geom_boxplot()
    ggplot(diamonds, aes(carat, price)) +
      geom_boxplot(aes(group = cut_width(carat, 0.25)))

    # It's possible to draw a boxplot with your own computations if you
    # use stat = "identity":
    y <- rnorm(100)
    df <- data.frame(
      x = 1,
      y0 = min(y),
      y25 = quantile(y, 0.25),
      y50 = median(y),
      y75 = quantile(y, 0.75),
      y100 = max(y)
    )
    ggplot(df, aes(x)) +
      geom_boxplot(
       aes(ymin = y0, lower = y25, middle = y50, upper = y75, ymax = y100),
       stat = "identity"
     )

[Package ggplot2 version 2.1.0 Index]