Python Pivot Chart Libraries Comparison

About This Project

This project compares four popular Python libraries for creating interactive pivot charts and data visualizations: PivotTable.js, hvPlot, Plotly, and Bokeh.

We use RPG game session data to demonstrate the capabilities of each library, showcasing how they handle data aggregation, interactivity, and visualization customization.

PivotTable.js

JavaScript library for creating interactive pivot tables in the browser.

Drag-and-drop interface
Multiple aggregation types
Custom renderers
Pure JavaScript

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hvPlot

High-level plotting API built on Bokeh and HoloViews.

Pandas-like syntax
Bokeh backend
Interactive widgets
Quick prototyping

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Plotly

Powerful library for creating interactive, publication-quality visualizations.

Rich chart types
Hover information
3D support
Statistical charts

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Bokeh

Interactive visualization library for modern web browsers.

Flexible API
Server-based apps
Large datasets
Custom interactions

View Example →