Python Graph Gallery
Check out plotly for general graphing use and bokeh for heavy loads.An exhaustive list of dataviz libraries is maintained at https://github.com/fasouto/awesome-datavizFor Python:  * altair - Declarative statistical visualizations, based on Vega-lite.
  * bokeh - Interactive Web Plotting for Python.
  * diagram - Text mode diagrams using UTF-8 characters
  * ggplot - plotting system based on R's ggplot2.
  * glumpy - OpenGL scientific visualizations library.
  * holoviews - Complex and declarative visualizations from annotated data.
  * matplotlib - 2D plotting library.
  * missingno - provides flexible toolset of data-visualization utilities that allows quick visual summary of the completeness of your dataset, based on matplotlib.
  * plotly - Interactive web based visualization built on top of plotly.js
  * plotnine - A grammar of graphics for Python
  * pygal - A dynamic SVG charting library.
  * PyQtGraph - Interactive and realtime 2D/3D/Image plotting and science/engineering widgets.
  * seaborn - A library for making attractive and informative statistical graphics.
  * toyplot - The kid-sized plotting toolkit for Python with grownup-sized goals.
  * Veusz - https://veusz.github.io
  * VisPy - High-performance scientific visualization based on OpenGL.