Wagtail-Plotly

Create charts in Wagtail using Plotly. This is project is in Alpha, so expect breaking changes!

Some more examples

Installation

Install from PyPI:

pip install wagtail-plotly

Then add the following to your project's INSTALLED_APPS.

'wagtail.contrib.table_block',
'generic_chooser',
'wagtail_color_panel',
'wagtail_plotly',

Out of the box

There are currently several plot blocks that are ready to use:

• BarChartBlock / LinePlotBlock
• ContourPlotBlock / HeatmapPlotBlock
• PieChartBlock
• ScatterPlotBlock

Each plot block has a number of trace/layout fields appropriate to its type.

Example use

One way of using it is to create a StreamBlock:

from wagtail.core import blocks

from wagtail_plotly.blocks.plot import (
    BarChartBlock,
    ContourPlotBlock,
    HeatmapPlotBlock,
    LinePlotBlock,
    PieChartBlock,
    ScatterPlotBlock,
)

class MyStreamBlock(blocks.StreamBlock):
    bar_chart = BarChartBlock()
    contour_plot = ContourPlotBlock()
    heatmap_plot = HeatmapPlotBlock()
    line_plot = LinePlotBlock()
    pie_chart = PieChartBlock()
    scatter_plot = ScatterPlotBlock()

Add the StreamBlock to a StreamField on a Wagtail page:

from wagtail.admin.edit_handlers import StreamFieldPanel
from wagtail.core.fields import StreamField
from wagtail.core.models import Page

from .blocks import MyStreamBlock


class MyPage(Page):

    body = StreamField(MyStreamBlock(), null=True)

    content_panels = Page.content_panels + [
        StreamFieldPanel('body'),
    ]

Then in the page template:

{% load static wagtailcore_tags %}

{% include_block page.body %}

Build your own

The plots in wagtail-plotly are based around a set of base block classes, that can be extended to create your own plots. The intention is to allow custom layouts and trace config whilst handling the data input. The base classes are:

• BaseBarChartBlock
• BaseContourPlotBlock
• BaseHeatmapPlotBlock
• BaseLinePlotBlock
• BasePieChartBlock
• BaseScatterPlotBlock

Each base block class inherits from BasePlotBlock. All of the blocks have a plot_data field for entering plot data (based on wagtail.contrib.table_block) and build_data method for extracting data from the table ready for plotting.

Creating new plot blocks

New plot blocks can be created by inheriting from a base plot. The get_trace_fields and get_layout_fields methods can be used to pass any additional fields to the Plotly update_traces and update_layout methods respectively.

Note: It's important that the field names are based on parameters that Plotly knows about, see https://plotly.com/python/reference/ for details.

A basic bar chart block might look like this:

class MyBarChartBlock(BaseBarChartBlock):
    orientation = blocks.ChoiceBlock(default='v', choices=[
        ('v', 'Vertical'), ('h', 'Horizontal')
    ])

    barmode = blocks.ChoiceBlock(default='group', choices=[
        ('group', 'Group'), ('stack', 'Stack'),
    ])

    def get_trace_fields(self):
        return ['orientation']

    def get_layout_fields(self):
        return ['barmode']

Admin interface

wagtail-plotly is installed as a separate items in the Wagtail admin menu. It currently only has two options, Palettes and Layouts.

Palettes

Palettes consist of a selection of colors that are used to draw the plots. Any number of palettes can be created. A user defined Palette can be selected in a Layout for the colorway field.

Layouts

Layouts control the look, style and positioning of the wagtail-plotly plot elements. There are settings for controlling title layout, fonts, legends and margins. Not all of Plotly's layout options are covered, but this provides a simple way to add user defined layouts to your plot blocks using a LayoutChooserBlock.

LayoutChooserBlock

The layout is a special named field that can be added to a plot block using the LayoutChooserBlock, allowing the selection of user defined layouts.