panel-highcharts 20210816.1

A python package enabling you to use HighCharts with Jupyter, HoloViz Panel and the rest of the tools you know and love

📈 Panel HighCharts

The panel-highcharts package makes it easy to use Highcharts from Python for exploratory analysis in a Jupyter Notebook or as a HoloViz Panel Web App.

Check out the panel-highcharts examples on Binder or the article Highly Interactive Data Visualization.

Jupyter Notebook	Jupyter Labs	Panel Apps

🏁 Background

This project was started because a colleague of mine loves to use HighCharts for his analytics trading apps. As there was no really easy way of using HighCharts in Python, Notebooks or Panel, it would be difficult for me, my team and our traders to collaborate. So I created this package in my spare time as an open source project to share with the world.

⚖️ License

The panel-highcharts python package and repository is open source and free to use (MIT License), however Highcharts itself requires a license for commercial use. For more info see the Highcharts license FAQs.

🏃 Getting Started

With pip

pip install panel-highcharts

From within a Jupyter Notebook

import panel_highcharts as ph

import panel as pn
pn.extension('highchart')

configuration = {
    "title": {"text": "HighChart Pane"},
    "series": [
        {
            "name": "series1",
            "data": [1, 2, 3, 4, 5],
        }
    ]
}

ph.HighChart(object=configuration, sizing_mode="stretch_width")

👩‍🏫 Reference Guides

Guide	Notebook	Jupyter Notebook	Jupyter Labs	Panel App
HighChart	View
HighStock	View
HighMap	View
HighGantt	View

🎨 Gallery

Guide	Notebook	Jupyter Notebook	Jupyter Labs	App	App
AddSeriesDynamically	View
Network	View				Awesome Panel
PackedBubble	View

| Variwide | View | | | | |

💡 Inspiration

You can find more inspiration via

• Awesome Panel
• Highcharts, Demos
• Highly Interactive Data Visualization
• Panel

🛣️ Roadmap

When I get the time I would like to

• Support pandas .plot api via method as .highplot on dataframes
• Add more examples
• Add badges for 100% test coverage etc.
• Distribute as conda package

📰 Change Log

• 20210816: Upgrade to panel 0.12.1 and support Variwide Chart
• 20210724: Work around https://github.com/holoviz/panel/issues/2571
• 20210724: Upgraded to Panel 0.12.0 and Bokeh 2.3.3
• 20210619: Add add_series method
• 20210517: Add PackedBubble example
• 20210405: Add HighStock, HighMap, HighGantt
• 20210404: Can now display in Classic Notebook
• 20210403: First Release to PyPi. Works in Jupyter Lab and Panel App.