Plotting
Basics
Bokeh.figure
— Functionfigure(; ...)
Create a new Figure
and return it.
Acceptable keyword arguments are:
- Anything taken by
Figure
. x_range
/y_range
: Sets the x/y-range. May be a vector of factors or a 2-tuple representing an interval. Default:DataRange1d()
.x_axis
/y_axis
: Sets the x/y-axis. May benothing
to suppress. Default:LinearAxis()
.x_axis_location
/y_axis_location
: Where to put the axis. One of"left"
,"right"
,"above"
or"below"
. Default:"below"
/"left"
.x_axis_label
/y_axis_label
: Sets the label on the x/y-axis.x_grid
/y_grid
: Sets the x/y-grid. May benothing
to suppress.tools
: Optional list of tools to create a toolbar from.tooltips
: If given, add aHoverTool
with these tooltips.
Bokeh.plot!
— Functionplot!(plot, item; ...)
plot!(plot, type; ...)
Adds a new item to the plot, or an item of the given type.
When passing a type, the allowed keyword arguments include anything accepted by the type. Some additional arguments are allowed depending on what item
or type
is.
The constructed item is returned. In the case of glyphs, the corresponding GlyphRenderer
is returned instead.
Glyphs
Additional keyword arguments:
- Anything accepted by
GlyphRenderer
. source
: Alias fordata_source
. May be aDataSource
,Dict
of columns, or aTables.jl
-style table.color
: Alias for all the*_color
properties.alpha
: Alias for all the*_alpha
properties.palette
: If the glyph has acolor_mapper
property, it is set to aLinearColorMapper
with this palette.legend_label
legend_field
legend_group
filters
: List of filters to apply to the source data.
Renderers
This includes axes, grids, legends and other annotations.
Additional keyword arguments:
location
: One of"center"
(default),"left"
,"right"
,"below"
or"above"
.dimension
: For axes, you must specify either thelocation
ordimension
and the other one is inferred.
Tools
Additional keyword arguments:
activate
: If true, then set the tool as the active one of its kind on the toolbar.
Layouts
Bokeh.column
— Functioncolumn(items; ...)
column(items...; ...)
Create a new Column
with the given items.
Bokeh.row
— Functionrow(items; ...)
row(items...; ...)
Create a new Row
with the given items.
Bokeh.grid
— Functiongrid(items; ...)
grid(items...; ...)
Create a GridBox
from the given items.
The items
argument is one of:
- A vector of other items. The top-level vector arranges its items in a column. Subsequent nesting of vectors switch between rows and columns, making it easy to create complex layouts.
- A matrix, specifying two levels of nesting.
- A
LayoutDOM
object, which is the terminal entry in the grid. - A
Row
orColumn
, explicitly specifying a row or column of the grid. nothing
, representing a blank cell.
Keyword arguments
sizing_mode
: How the resulting grid is sized.nrows
orncols
: Ifitems
is a vector and one of these arguments is specified, it is partitioned into a 2D layout with the given number of rows or columns.item_width
,item_height
: The width and height of each item.merge_tools=true
: When true, toolbars of constituent plots are merged into one.toolbar_location="above"
: Where to place the merged toolbar. May benothing
.toolbar_options
: A named tuple of options for the merged toolbar.- Remaining arguments are passed to
GridBox
.
Bokeh.widgetbox
— Functionwidgetbox(items; ...)
widgetbox(items...; ...)
Create a new WidgetBox
with the given items.
Transforms
These can be used as the value for properties such as fill_color
or mark
.
Bokeh.dodge
— Functiondodge(field, value; kw...)
Transform the given field with a Dodge
.
Bokeh.factor_cmap
— Functionfactor_cmap(field, palette, factors; ...)
Transform the given field with a CategoricalColorMapper
that selects the given colors for the corresponding factors.
Bokeh.factor_mark
— Functionfactor_mark(field, markers, factors; ...)
Transform the given field with a CategoricalMarkerMapper
that selects the given markers for the corresponding factors.
Bokeh.factor_hatch
— Functionfactor_hatch(field, patterns, factors; ...)
Transform the given field with a CategoricalPatternMapper
that selects the given hatch patterns for the corresponding factors.
Bokeh.jitter
— Functionjitter(field, width; ...)
Transform the given field with a Jitter
that applies random pertubations of the given width.
Bokeh.linear_cmap
— Functionlinear_cmap(field, palette; ...)
Transform the given field with a LinearColorMapper
that selects colors linearly from the given palette.
Bokeh.log_cmap
— Functionlog_cmap(field, palette; ...)
Transform the given field with a LogColorMapper
that selects colors logarithmically from the given palette.
Bokeh.transform
— Functiontransform(field, transform)
A the field of the given name transformed with the given Transform
.