Python Graph Gallery

This is great! I will bookmark it. I really like two things: first, the progression from simple to more complex figures. Matplotlib's documentation has the tendency to give very complicated examples. Second I think it's great it spans several libraries.

Re: Python Graph Gallery

#7

Post by dagurp » Mon, Oct 16, 2017, 10:04 AM UTC

krock wrote: post #3

omegote wrote: post #2

Aaaand it's gone.

looks like it's back

And gone again

Re: Python Graph Gallery

#8

Post by Toenex » Mon, Oct 16, 2017, 10:11 AM UTC

dagurp wrote: post #7

krock wrote: post #3

Earlier quoted context omitted.

looks like it's back

And gone again

Back and yet gone too. HN effect in full effect.

Re: Python Graph Gallery

#9

Post by Dowwie » Mon, Oct 16, 2017, 10:39 AM UTC

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-dataviz

For 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.

Re: Python Graph Gallery

#10

Post by xioxox » Mon, Oct 16, 2017, 11:24 AM UTC

Dowwie wrote: post #9

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-dataviz For 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…

It's missing the Veusz multiplatform GUI plotting package and associated Python plotting library: https://veusz.github.io/ (I am the main author)

The saved files in Veusz are basically Python scripts which reproduce the plot. Plots are built by putting together different types of plotting widgets. These widgets can have their appearance and properties changed in the GUI. The program can also do various types of basic data analysis within the GUI. Plugins can be added for supporting different data formats, manipulating data or automating tasks.