About Highcharts for Python

High-end data visualization for the Python ecosystem.

Highcharts for Python is a collection of Python libraries that gives you access to all the rich features of Highcharts Core (formerly Highcharts JS), Highcharts Stock, Highcharts Maps and Highcharts Gantt via a simple, Pythonic API. Produce spectacular charts in no time thanks to simple syntax, intuitive function names, and direct integration with data tools like Pandas and Jupyter Notebooks. Highcharts for Python integrates with the most popular components of the Python data science ecosystem. Every Highcharts visualization can be constructed from a Pandas or PySpark DataFrame with one method call, and then rendered in Jupyter Labs/Notebooks using another method call.

Comprehensive Highcharts Support
Highcharts for Python, provides the full set of rich options, customizations, and interactivity provided by the Highcharts JavaScript libraries. Eliminating the need for "piecing together" partial solutions from unmaintained community libraries. Using a simple Pythonic API, the toolkit makes tapping into Highcharts features fast and simple - "batteries included" with full support for rich callback and formatter functions, SVG extensions, and more.

Simple and Powerful Pythonic API
Highcharts for Python does the heavy lifting of providing a truly Pythonic API. No need to rely on "hacky" solutions involving gigantic Python dict’s, JSON files that only support part of the Highcharts JavaScript capabilities, or switching back and forth between Pythonic snake_case and JavaScript camelCase.

Simple UI Integration
Highcharts for Python is designed to simplify the integration of your (often back-end) Python code with your UI code. With one method call, you can generate the full set of JavaScript code that should be rendered by your UI to display the fully-configured data visualizations your applications need.

Easy and Consistent Chart Downloads
Download static versions of your data visualizations using all of their Highcharts formatting and configuration with just one method call. Easily export your charts to PNG, JPG, PDF, SVG, and more.

Native Integration with the Python Ecosystem
Using Highcharts for Python, you can easily integrate rich Highcharts visualizations into your Python stack taking advantage of native integrations with:

  • Jupyter Labs/Jupyter Notebooks
  • Pandas
  • PySpark
  • GeoPandas
  • and more

Using the Python toolkit, you can easily leverage Highcharts in your exploratory data analysis (EDA) workflows, and use popular components of the modern data stack such as Databricks.

Highcharts for Python integrates with Highcharts Core, Highcharts Stock, Highcharts Maps and Highcharts Gantt.

  • Highcharts Core for Python - This is the core library. It provides full support for the Highcharts Core JavaScript library, and serves as the foundation for the entire Highcharts for Python toolkit.
  • Highcharts Stock for Python - The Highcharts Stock for Python library extends the Highcharts Core Python library with full support for the Highcharts Stock JavaScript library. It includes the Highcharts Core Python library, but extends its functionality with over 40 technical indicators, in-chart navigation and timelines, and rich tools for in-chart analysis and annotation of data.
  • Highcharts Maps for Python - The Highcharts Maps for Python library extends the Highcharts Core Python library with full support for the Highcharts Maps JavaScript library. It includes the Highcharts Core Python library, but extends its functionality with full TopoJSON and GeoJSON support, rich map projection and visualization capabilities, and native integration with GeoPandas for GIS data analysis.
  • Highcharts Gantt for Python - The Highcharts Gantt for Python library extends the Highcharts Core Python library with full support for the Highcharts Gantt JavaScript library. It includes the Highcharts Stock Python library, and extends its functionality with native integrations with JIRA, Asana, and Monday.com.