A Python plotting library that generates interactive D3.js visualizations from pandas DataFrames.
d3py is a Python plotting library that creates interactive, browser-based visualizations using D3.js. It enables data scientists and developers to generate charts directly from pandas DataFrames or NetworkX graphs, serving them locally for immediate viewing and customization. The library mimics the layered grammar of graphics from ggplot2, providing an intuitive API for building complex plots.
Python developers and data analysts who work with pandas or NetworkX and want to create interactive, web-ready visualizations without writing JavaScript. It's ideal for those exploring D3.js-based plotting from Python scripts or command-line tools.
d3py offers a straightforward bridge between Python data analysis and D3.js visualizations, allowing users to leverage pandas' data structures while producing interactive, stylable charts. Its emphasis on clean, exportable code and live browser styling sets it apart from static plotting libraries.
a plottling library for python, based on D3
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Seamlessly plots data from pandas DataFrames and NetworkX graphs, as shown in examples using DataFrames for scatter plots and graphs for network visualizations.
Generates SVG-based, interactive visualizations using D3.js, enabling browser-served charts with the .show() method for immediate inspection.
Uses a declarative, layered grammar of graphics inspired by ggplot2, allowing intuitive plot construction by adding geoms like Point and Line.
Supports real-time CSS customization via browser developer tools, as mentioned in the README for tweaking plots on the fly without code changes.
Outputs clean HTML, CSS, JSON, and JavaScript files through .show(), making it easy to embed visualizations into websites with minimal overhead.
The author admits it's an experiment from 2013 and recommends vincent instead, indicating no updates, which risks bugs and compatibility issues with modern dependencies.
Only basic geoms like Point, Line, Bar, and Area are demonstrated, with missing support for advanced D3.js visualizations or customization options like size parameters.
Requires manual installation of pandas, numpy, and networkx via pip, adding complexity compared to single-package plotting libraries with bundled dependencies.
The README is brief and outdated, with few examples beyond basic plots, making it challenging to troubleshoot or extend for complex use cases.