R: Display binned data

layer_histograms {ggvis} | R Documentation

## Display binned data

### Description

Display binned data

### Usage

    layer_histograms(vis, ..., width = NULL, center = NULL, boundary = NULL,
      closed = c("right", "left"), stack = TRUE, binwidth)

    layer_freqpolys(vis, ..., width = NULL, center = NULL, boundary = NULL,
      closed = c("right", "left"), binwidth)

### Arguments

`vis` | Visualisation to modify
`...` | Visual properties used to override defaults.
`width` | The width of the bins. The default is `NULL`, which yields 30 bins that cover the range of the data. You should always override this value, exploring multiple widths to find the best to illustrate the stories in your data.
`center` | The center of one of the bins. Note that if center is above or below the range of the data, things will be shifted by an appropriate number of `width`s. To center on integers, for example, use `width=1` and `center=0`, even if `0` is outside the range of the data. At most one of `center` and `boundary` may be specified.
`boundary` | A boundary between two bins. As with `center`, things are shifted when `boundary` is outside the range of the data. For example, to center on integers, use `width = 1` and `boundary = 0.5`, even if `1` is outside the range of the data. At most one of `center` and `boundary` may be specified.
`closed` | One of `"right"` or `"left"` indicating whether right or left edges of bins are included in the bin.
`stack` | If `TRUE`, will automatically stack overlapping bars.
`binwidth` | Deprecated; use `width` instead.

### See Also

`layer_bars` For bar graphs of counts at each unique x value, in contrast to a histogram's bins along x ranges.

### Examples

    # Create histograms and frequency polygons with layers
    mtcars %>% ggvis(~mpg) %>% layer_histograms()
    mtcars %>% ggvis(~mpg) %>% layer_histograms(width = 2)
    mtcars %>% ggvis(~mpg) %>% layer_freqpolys(width = 2)

    # These are equivalent to combining compute_bin with the corresponding
    # mark
    mtcars %>% compute_bin(~mpg) %>% ggvis(~x_, ~count_) %>% layer_paths()

    # With grouping
    mtcars %>% ggvis(~mpg, fill = ~factor(cyl)) %>% group_by(cyl) %>%
      layer_histograms(width = 2)
    mtcars %>% ggvis(~mpg, stroke = ~factor(cyl)) %>% group_by(cyl) %>%
      layer_freqpolys(width = 2)

[Package ggvis version 0.4.3 Index]