pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
See matplotlib_intro.py See matplotlib_example.py See matplotlib_csv_example.py
Pygal creates interactive SVG charts using python.
See pygal_intro.py See pygal_json_example.py See pygal_github_api_example.py See pygal_hn_api_example.py
Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets. Bokeh can help anyone who would like to quickly and easily make interactive plots, dashboards, and data applications.
See bokeh_example.py
folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the leaflet.js library. Manipulate your data in Python, then visualize it in on a Leaflet map via folium.
Plotly is an open source python graphing library
ggplot is a plotting system for Python based on R's ggplot2 and the Grammar of Graphics. It is built for making professional looking, plots quickly with minimal code.
VisPy VisPy is a Python library for interactive scientific visualization that is designed to be fast, scalable, and easy to use.
Altair is a declarative statistical visualization library for Python, based on Vega and Vega-Lite, and the source is available on GitHub.