rbokeh (version 0.5.2)

ly_bar: Add a "barchart" layer to a Bokeh figure

Description

Draws a bar chart

Usage

ly_bar(
  fig,
  x = NULL,
  y = NULL,
  data = figure_data(fig),
  color = NULL,
  alpha = 1,
  position = c("stack", "fill", "dodge"),
  width = 0.9,
  hover = FALSE,
  origin = NULL,
  breaks = NULL,
  right = FALSE,
  binwidth = NULL,
  lname = NULL,
  lgroup = NULL,
  legend = NULL,
  ...
)

Arguments

fig

figure to modify

x

values or field name for x variable, or if NULL, x-axis will be counts of y

y

values or field name for y variable, or if NULL, y-axis will be counts of x

data

an optional data frame, providing the source for inputs x, y, and color properties

color

color for the glyph - a hex code (with no alpha) or any of the 147 named CSS colors, e.g 'green', 'indigo' - for glyphs with both fill and line properties, see "Handling color" below

alpha

the alpha transparency of the glyph between 0 (transparent) and 1 (opaque) - if glyph has both fill and color properties, see "Handling alpha" below

position

either "stack", "fill", or "dodge" (see details)

width

with of each bar, a value between 0 (no width) and 1 (full width)

hover

logical - should a hover tool be added to show the value of each bar?

origin, breaks, right, binwidth

parameters to be used for binning x when it is continuous (not yet implemented)

lname

layer name

lgroup

layer group

legend

either a logical specifying not to plot a legend for this layer (FALSE) or a string indicating the name of the legend entry for this layer (note that when mapping plot attributes to variables in data, a legend is automatically created and does not need to be specified - see "Mapped plot attributes and legends" below)

…

additional parameters for fine control over fill and line properties (see "Additional parameters" below)

Handling color

The color parameter is a high-level plot attribute that provides default behavior for coloring glyphs.

• When using a glyph that only has line properties, this will be the color of the line.

• When using a glyph that has has line and fill properties, this will be the color of the line and the fill, with the alpha level of the fill reduced by 50%.

• If full control over fill and line color is desired, the fill_color and line_color attributes can be specified explicitly and will override color.

When color is NULL and fill_color or line_color are not specified, the color will be chosen from the theme.

Handling alpha

The alpha is a high-level plot attribute that sets the transparency of the glyph being plotted.

• When using a glyph that only has line properties, this will be the alpha of the line.

• When using a glyph that has has line and fill properties, this will be the alpha of the line and the alpha of the fill will be set to 50% of this value.

• Individual fill and line alpha can be specified with fill_alpha and line_alpha and will override alpha.

Mapped plot attributes and legends

When specifying an input data frame for a layer through the data argument, columns of data can be used to specify various plot attributes such as color, etc. For example, with ly_points(..., data = iris, color = Species), the Species variable is used to determine how to color the points. Here, Species is "mapped" to the color attribute. Both continuous and categorical variables can be mapped. In the case of continuous variables, the range is cut into slices and attributes are applied to each interval. The mapping from the values of the variable to the actual plot attributes is determined based on the theme.

Additional parameters

fill_color	color to use to fill the glyph with - a hex code (with no alpha) or any of the 147 named CSS colors, e.g 'green', 'indigo'
fill_alpha	transparency value between 0 (transparent) and 1 (opaque)
line_color	color to use to stroke lines with - a hex code (with no alpha) or any of the 147 named CSS colors, e.g 'green', 'indigo'
line_width	stroke width in units of pixels
line_alpha	transparency value between 0 (transparent) and 1 (opaque)
line_join	how path segments should be joined together 'miter' 'round' 'bevel'
line_cap	how path segments should be terminated 'butt' 'round' 'square'
line_dash	array of integer pixel distances that describe the on-off pattern of dashing to use

Details

This function expects one of either x or y to be categorical and the other to be numeric or NULL. The numeric variable is summed for each categorical variable and bars are plotted. If no numeric variable is supplied, the unique values of the categorical variable will be tabulated. Within each categorical variable, if color maps to another grouping variable then the bars are split up. In this case, there are three ways to display the bars with the position argument. The default, "stack" will stack the bars. The "fill" choice will show the relative proportion for each group within each categorical variable level, stacking the bars. The "dodge" choice will plot the bars for each level of the categorical variable side by side.

See Also

Other layer functions: ly_abline(), ly_annular_wedge(), ly_annulus(), ly_arc(), ly_bezier(), ly_boxplot(), ly_contour(), ly_crect(), ly_curve(), ly_density(), ly_hist(), ly_image_url(), ly_image(), ly_lines(), ly_map(), ly_multi_line(), ly_oval(), ly_patch(), ly_points(), ly_polygons(), ly_quadratic(), ly_quantile(), ly_ray(), ly_rect(), ly_segments(), ly_text(), ly_wedge()

Examples

# NOT RUN {
# count of variety
figure() %>%
  ly_bar(variety, data = lattice::barley) %>%
  theme_axis("x", major_label_orientation = 90)

# total yield per variety
figure() %>%
  ly_bar(variety, yield, data = lattice::barley, hover = TRUE) %>%
  theme_axis("x", major_label_orientation = 90)

# swap axes and add hover
figure() %>%
  ly_bar(yield, variety, data = lattice::barley, hover = TRUE)

# stack by year
figure() %>%
  ly_bar(variety, yield, color = year, data = lattice::barley, hover = TRUE) %>%
  theme_axis("x", major_label_orientation = 90)

# proportional bars
figure() %>%
  ly_bar(variety, yield, color = year,
    data = lattice::barley, position = "fill", width = 1) %>%
  theme_axis("x", major_label_orientation = 90) %>%
  set_palette(discrete_color = pal_color(c("red", "blue")))

# swap axes and use different palette
figure() %>%
  ly_bar(yield, variety, color = year,
    data = lattice::barley, position = "fill") %>%
  set_palette(discrete_color = pal_color(c("red", "blue")))

# side by side bars
figure() %>%
  ly_bar(variety, yield, color = year,
    data = lattice::barley, position = "dodge") %>%
  theme_axis("x", major_label_orientation = 90)

# use a different theme
figure() %>%
  ly_bar(variety, yield, color = year,
    data = lattice::barley, position = "dodge") %>%
  theme_axis("x", major_label_orientation = 90)
# }