MkDocs plugin to create plots from data using the declarative vegalite syntax. This makes it easier to build reproducible reports with MkDocs.

👉 See it in action on the demo page

Includes supports for mkdocs-material theme features like instant loading and dark color themes.

Install the plugin using pip3:

pip3 install mkdocs-charts-plugin

Next, add the following lines to your mkdocs.yml:

plugins:
  - search
  - charts
extra_javascript:
  - https://cdn.jsdelivr.net/npm/vega@5
  - https://cdn.jsdelivr.net/npm/vega-lite@5
  - https://cdn.jsdelivr.net/npm/vega-embed@6
markdown_extensions:
  - pymdownx.superfences:
      custom_fences:
        - name: vegalite
          class: vegalite
          format: !!python/name:mkdocs_charts_plugin.fences.fence_vegalite

If you have no plugins entry in your config file yet, you'll likely also want to add the search plugin. MkDocs enables it by default if there is no plugins entry set.

You can insert any valid vegalite JSON into a markdown file. But the real magic is that you can visualize .json or .csv files:

```vegalite 
{
  "description": "A simple bar chart with embedded data.",
  "data": {"url" : "assets/charts/data/basic_bar_chart.json"},
  "mark": {"type": "bar", "tooltip": true},
  "encoding": {
    "x": {"field": "a", "type": "nominal", "axis": {"labelAngle": 0}},
    "y": {"field": "b", "type": "quantitative"}
  }
}
```

See the vegalite editor for a range of examples.

See the documentation timvink.github.io/mkdocs-charts-plugin for examples, use cases and options.

Do checkout the other charting plugins for mkdocs that might suit your specific use-case better.