Interactive Data Visualization in the browser, from Python
Panel: The powerful data exploration & web app framework for Python
Python library that makes it easy for data scientists to create charts.
All the slides, accompanying code and exercises all stored in this repo. 🎈
Easy to use Python API wrapper to plot charts with matplotlib, plotly, bokeh and more
Plotting addon for backtrader to support Bokeh (and maybe more)
Lineage metadata API, artifacts streams, sandbox, API, and spaces for Polyaxon
Data exploration glue
btplotting provides plotting for backtests, optimization results and live data from backtrader.
🚤 Label data at scale. Fun and precision included.
An extension for rendering Bokeh content in JupyterLab notebooks
This repository provides everything you need to get started with Python for (social science) research.
A workshop on data visualization in Python with notebooks and exercises for following along. Slides contain all solutions.
Training Diary
web application for flight log analysis & review
JupyterHub extension for ContainDS Dashboards
Rendering Realistic Bokeh Images with PyNET
DirectX 11 graphics engine
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