Anaconda Enterprise: Documentation

# Laying out Plots and Widgets

Bokeh includes several layout options for arranging plots and widgets. They aim to make it quick to create your interactive data applications. At the heart of the layouts are three core objects Row, Column, and WidgetBox. While you can use these models directly, we recommend using the layout functions `row()`, `column()`, and `widgetbox()`.

The layout functions let you build a grid of plots and widgets. You can nest as many rows, columns, and plots together as you’d like. In addition, Bokeh layouts support a number of “sizing modes”. These sizing modes allow plots and widgets to resize based on the browser window.

There are two things to keep in mind for best results using layout:

- All items must have the same sizing mode.
- Widgets should be inside a widget box.

These guidelines are explained in more detail below:

Consistent sizing mode
  Every item in a layout must have the same sizing mode for the layout to behave as expected. It is for this reason that we recommend using the layout functions as they help ensure that all the children of the row or column have the same sizing mode. We hope to lift this restriction in future releases.
Widget boxes
  Widgets are HTML objects like buttons, and dropdown menus. They behave slightly differently to plots and and putting them in a widgetbox is necessary so that they can all work together. In fact, if you try and put a `Widget` in `Row` or `Column` it will be automatically put into a `WidgetBox`. As a result, it’s a good idea to wrap your own widgets in a``WidgetBox`` using `widgetbox()` as then you can be sure about how your widgets are getting arranged.

## Toolbars

For information about changing the position or orientation of plot toolbars, see Positioning the Toolbar section in the Configuring Plot Tools chapter of the User’s Guide.

## Columns

To display plots or widgets in a vertical fashion, use the `column()` function:

    from bokeh.io import output_file, show
    from bokeh.layouts import column
    from bokeh.plotting import figure

    output_file("layout.html")

    x = list(range(11))
    y0 = x
    y1 = [10 - i for i in x]
    y2 = [abs(i - 5) for i in x]

    # create a new plot
    s1 = figure(plot_width=250, plot_height=250, title=None)
    s1.circle(x, y0, size=10, color="navy", alpha=0.5)

    # create another one
    s2 = figure(plot_width=250, plot_height=250, title=None)
    s2.triangle(x, y1, size=10, color="firebrick", alpha=0.5)

    # create and another
    s3 = figure(plot_width=250, plot_height=250, title=None)
    s3.square(x, y2, size=10, color="olive", alpha=0.5)

    # put the results in a column and show
    show(column(s1, s2, s3))

## Rows

To display plots horizontally, use the `row()` function.

    from bokeh.io import output_file, show
    from bokeh.layouts import row
    from bokeh.plotting import figure

    output_file("layout.html")

    x = list(range(11))
    y0 = x
    y1 = [10 - i for i in x]
    y2 = [abs(i - 5) for i in x]

    # create a new plot
    s1 = figure(plot_width=250, plot_height=250, title=None)
    s1.circle(x, y0, size=10, color="navy", alpha=0.5)

    # create another one
    s2 = figure(plot_width=250, plot_height=250, title=None)
    s2.triangle(x, y1, size=10, color="firebrick", alpha=0.5)

    # create and another
    s3 = figure(plot_width=250, plot_height=250, title=None)
    s3.square(x, y2, size=10, color="olive", alpha=0.5)

    # put the results in a row
    show(row(s1, s2, s3))

## Widgets

Layout a group of widgets with the `widgetbox()` function.

    from bokeh.io import output_file, show
    from bokeh.layouts import widgetbox
    from bokeh.models.widgets import Button, RadioButtonGroup, Select, Slider

    output_file("layout_widgets.html")

    # create some widgets
    slider = Slider(start=0, end=10, value=1, step=.1, title="Slider")
    button_group = RadioButtonGroup(labels=["Option 1", "Option 2", "Option 3"], active=0)
    select = Select(title="Option:", value="foo", options=["foo", "bar", "baz", "quux"])
    button_1 = Button(label="Button 1")
    button_2 = Button(label="Button 2")

    # put the results in a row
    show(widgetbox(button_1, slider, button_group, select, button_2, width=300))

## Grids Layout for Plots

The `gridplot()` function can be used to arrange Bokeh Plots in grid layout. `gridplot()` also collects all tools into a single toolbar, and the currently active tool is the same for all plots in the grid. It is possible to leave “empty” spaces in the grid by passing `None` instead of a plot object.

    from bokeh.io import output_file, show
    from bokeh.layouts import gridplot
    from bokeh.palettes import Viridis3
    from bokeh.plotting import figure

    output_file("layout_grid.html")

    x = list(range(11))
    y0 = x
    y1 = [10 - i for i in x]
    y2 = [abs(i - 5) for i in x]

    # create three plots
    p1 = figure(plot_width=250, plot_height=250, title=None)
    p1.circle(x, y0, size=10, color=Viridis3[0])
    p2 = figure(plot_width=250, plot_height=250, title=None)
    p2.triangle(x, y1, size=10, color=Viridis3[1])
    p3 = figure(plot_width=250, plot_height=250, title=None)
    p3.square(x, y2, size=10, color=Viridis3[2])

    # make a grid
    grid = gridplot([[p1, p2], [None, p3]])

    # show the results
    show(grid)

For convenience you can also just pass a list of plots, and specify the number of columns you want in your grid. For example,

    gridplot([[s1, s2], [s3, None]])

and

    gridplot([s1, s2, s3], ncols=2)

are equivalent. In addition, you can pass in `plot_width` and `plot_height` arguments, and this will set the size of all your plots. By default, `gridplot` will merge all tools within each child plot to a single toolbar attached to the grid. To disable this behavior, you can set the option `merge_tools` to `False`.

Note

You cannot use `None` with the `ncols` argument. It must only be a list of `Plot` objects at once.

    from bokeh.io import output_file, show
    from bokeh.layouts import gridplot
    from bokeh.palettes import Viridis3
    from bokeh.plotting import figure

    output_file("layout_grid_convenient.html")

    x = list(range(11))
    y0 = x
    y1 = [10 - i for i in x]
    y2 = [abs(i - 5) for i in x]

    # create three plots
    s1 = figure()
    s1.circle(x, y0, size=10, color=Viridis3[0])
    s2 = figure()
    s2.triangle(x, y1, size=10, color=Viridis3[1])
    s3 = figure()
    s3.square(x, y2, size=10, color=Viridis3[2])

    # make a grid
    grid = gridplot([s1, s2, s3], ncols=2, plot_width=250, plot_height=250)

    # show the results
    show(grid)

## General Grid Layout

The `layout()` function can be used to arrange both Plots and Widgets in a grid, generating the necessary `row()` and `column()` layouts automatically. This allows for quickly spelling a layout like this:

    l = layout([
      [bollinger],
      [sliders, plot],
      [p1, p2, p3],
    ], sizing_mode='stretch_both')

Which produces the following layout:

The full code for this plot is available at examples/howto/layouts/dashboard.py in the project GitHub repository.