Best Open Source Python Charting Libraries

Python Charting Libraries

Charting Libraries Python Clear Filters

Browse free open source Python Charting Libraries and projects below. Use the toggles on the left to filter open source Python Charting Libraries by OS, license, language, programming language, and project status.

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1

plotly.py

The interactive graphing library for Python

plotly.py is a browser-based, open source graphing library for Python that lets you create beautiful, interactive, publication-quality graphs. Built on top of plotly.js, it is a high-level, declarative charting library that ships with more than 30 chart types. Everything from statistical charts and scientific charts, through to maps, 3D graphs and animations, plotly.py lets you create them all. Graphs made with plotly.py can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using Chart Studio Cloud.

Downloads: 1 This Week

Last Update: 4 days ago
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2

Django REST Pandas

Serves up Pandas dataframes via the Django REST Framework

Django REST Pandas (DRP) provides a simple way to generate and serve pandas DataFrames via the Django REST Framework. The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This capability can often be leveraged by sending users to the same URL that your visualization code uses internally to load the data. While DRP is primarily a data API, it also provides a default collection of interactive visualizations through the @wq/chart library, and a @wq/pandas loader to facilitate custom JavaScript charts that work well with CSV output served by DRP. These can be used to create interactive time series, scatter, and box plot charts.

Downloads: 0 This Week

Last Update: 2022-09-02
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