5 ms·

Python Graph Gallery

279 points by sebst 9y ago

omegote 9y ago
Aaaand it's gone.
- krock 9y ago
  looks like it's back
  - dagurp 9y ago
    And gone again
    - Toenex 9y ago
      Back and yet gone too. HN effect in full effect.
- papey 9y ago
  Yep.
hathym 9y ago
looks awesome, thank you
plafl 9y ago
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.
Dowwie 9y ago
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 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.
- xioxox 9y ago
  It's missing the Veusz multiplatform GUI plotting package and associated Python plotting library: https://veusz.github.io/ 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.
  - deleted 9y ago
    [deleted]
  - Dowwie 9y ago
    do you not know how to fork , update, and submit a PR? if not, now you do
    - xioxox 9y ago
      If you had checked the repository, you would have seen that I had already done that. I posted here the link to add your list.
      - Dowwie 9y ago
        https://github.com/fasouto/awesome-dataviz/pull/40 https://github.com/fasouto/awesome-dataviz/pull/40
- eyeball 9y ago
  https://plotnine.readthedocs.io/en/stable/ https://plotnine.readthedocs.io/en/stable/
  - deleted 9y ago
    [deleted]
- 9y ago
deleted 9y ago
[deleted]
fnord123 9y ago
bad charts link is broken. Missing gantt charts. These are good for plotting logs in distributed systems so you can line up the events. Sadly you have to use hbox in matplotlib which isn't ideal (but it works).
- fnord123 9y ago
  bad charts link was fixed. Gantt charts can be done using the lollipop example: https://python-graph-gallery.com/184-lollipop-plot-with-2-groups/ https://python-graph-gallery.com/184-lollipop-plot-with-2-gr...
edraferi 9y ago
Very cool resource, thanks for putting it out there. Noticed a couple areas for improvement: Contribution instructions: Per the contributors page, it looks like an email is the way to go [0]. It would be nice to be able to run the standard Github workflow, but the relevant repo seems abandoned [1] Site performance: The site looks good and has strong content, but loads slowly & inconsistently. (could just be the hug of death). Chrome warns the page is loading unauthenticated resources. I suggest you look at using a static website deployed to a CDN. Github pages, Netlify [2], etc are reasonable ways to do that. If you want comments, you can do that on Github. [0] https://python-graph-gallery.com/contributors/ https://python-graph-gallery.com/contributors/ [1] https://github.com/holtzy/The-Python-Graph-Gallery https://github.com/holtzy/The-Python-Graph-Gallery [2] https://www.netlify.com/ https://www.netlify.com/
lincolnfrias 9y ago
Awesome. Very useful resource.

279 points by sebst 9y ago

omegote 9y ago

Aaaand it's gone.

krock 9y ago
looks like it's back
- dagurp 9y ago
  And gone again
  - Toenex 9y ago
    Back and yet gone too. HN effect in full effect.
papey 9y ago
Yep.

hathym 9y ago

looks awesome, thank you

plafl 9y ago

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.

Dowwie 9y ago

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 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.

xioxox 9y ago
It's missing the Veusz multiplatform GUI plotting package and associated Python plotting library: https://veusz.github.io/ 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.
- deleted 9y ago
  [deleted]
- Dowwie 9y ago
  do you not know how to fork , update, and submit a PR? if not, now you do
  - xioxox 9y ago
    If you had checked the repository, you would have seen that I had already done that. I posted here the link to add your list.
    - Dowwie 9y ago
      https://github.com/fasouto/awesome-dataviz/pull/40 https://github.com/fasouto/awesome-dataviz/pull/40
eyeball 9y ago
https://plotnine.readthedocs.io/en/stable/ https://plotnine.readthedocs.io/en/stable/
- deleted 9y ago
  [deleted]
9y ago

deleted 9y ago

[deleted]

fnord123 9y ago

bad charts link is broken. Missing gantt charts. These are good for plotting logs in distributed systems so you can line up the events. Sadly you have to use hbox in matplotlib which isn't ideal (but it works).

fnord123 9y ago
bad charts link was fixed. Gantt charts can be done using the lollipop example: https://python-graph-gallery.com/184-lollipop-plot-with-2-groups/ https://python-graph-gallery.com/184-lollipop-plot-with-2-gr...

edraferi 9y ago

Very cool resource, thanks for putting it out there. Noticed a couple areas for improvement: Contribution instructions: Per the contributors page, it looks like an email is the way to go [0]. It would be nice to be able to run the standard Github workflow, but the relevant repo seems abandoned [1] Site performance: The site looks good and has strong content, but loads slowly & inconsistently. (could just be the hug of death). Chrome warns the page is loading unauthenticated resources. I suggest you look at using a static website deployed to a CDN. Github pages, Netlify [2], etc are reasonable ways to do that. If you want comments, you can do that on Github. [0] https://python-graph-gallery.com/contributors/ https://python-graph-gallery.com/contributors/ [1] https://github.com/holtzy/The-Python-Graph-Gallery https://github.com/holtzy/The-Python-Graph-Gallery [2] https://www.netlify.com/ https://www.netlify.com/

lincolnfrias 9y ago

Awesome. Very useful resource.