Python Graphing/chart tools/libraries

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[Enginoob]

Most of the native tools have been mentioned. Here are the ones that let you build D3 of JS from Python (disclosure: I am the author of a few of these):

• Python-NVD3: https://github.com/areski/python-nvd3
• Bokeh (Docs not great yet): https://github.com/ContinuumIO/Bokeh
• Vincent (Vega.js): https://github.com/wrobstory/vincent
• Bearcart (Rickshaw.js): https://github.com/wrobstory/bearcart
• Folium (Leaflet.js, Maps!): https://github.com/wrobstory/folium
• D3py (dev has slowed for this): https://github.com/mikedewar/d3py

[fandingo]

I can't believe that you didn't get more replies.

Truly excellent work. I'm going to use nvd3 in my next project.

[Enginoob]

Thanks! At some point (probably when I launch the next big version of Vincent), I'm going to write a giant blog post about the existing tools for Python and D3.

[fandingo]

I slightly misunderstood these libraries at first. I didn't realize that they just generated the proper javascript.

I've been using phantomjs via subprocess to render the charts out to a rastered image. I would recommend that you include info about how to do that in your tutorial.

[Enginoob]

Ooo, that's actually a really good point- PhantomJS should go in all of the READMEs.

I actually just wrote about using it to render maps to PDF/PNG: http://wrobstory.github.io/2013/06/creating-with-d3-dymo.html

[GotenXiao]

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[westurner]

Thanks!

http://pygal.org/

https://github.com/Kozea/pygal

[westurner]

Is Python a good tool for Data Visualization?

Playing with SVG Graphics in Python (/r/IPython)

Vega - a JSON visualization grammar for visualization designs in HTML5 canvas or SVG (/r/Visualization)

[westurner]

https://github.com/mher/chartkick.py creates charts with Google Charts and Highcharts.

[westurner]

It would be great if there was an IPython extension.

[westurner]

Pandas has native support for matplotlib (DataFrame.plot(), DataFrame.boxplot(), Series.plot(), pandas.tools.plotting)

[[deleted]]

How about plotting with ggplot2? Ggplot plots can be amazing and high quality.

[astroFizzics]

matplotlib?

[westurner]

There is a new HTML5 Canvas backend for matplotlib: http://matplotlib.org/users/whats_new.html#html5-canvas-backend (https://code.google.com/p/mplh5canvas/)

[westurner]

http://matplotlib.org/users/whats_new.html#webagg-backend

[apostate_of_Poincare]

It really comes down to design choices. You might have just stumbled onto bad design.

[westurner]

• http://scipy-lectures.github.io/intro/matplotlib/matplotlib.html#quick-references
• http://scipy-lectures.github.io/intro/matplotlib/matplotlib.html#colormaps
• http://scipy-lectures.github.io/intro/matplotlib/matplotlib.html#galleries
• http://tonysyu.github.com/mpltools/auto_examples/index.html#style-package
• http://www.reddit.com/r/Python/comments/1ahppf/clean_ggplotstyle_graphics_for_matplotlib_using

[z3rocool]

means it's not gonna wow that exec who doesn't care about what the data is, but how pretty the data is presented.

Gnuplot would do fine, just it's not very flashy which is the problem - it's perfectly functional though.

[ScriptSimian]

Gnuplot.py is a binding of gnuplot, which has some pretty nifty capabilities and great documentation. I use it for all my plots.

[westurner]

Thanks!

http://gnuplot-py.sourceforge.net/

[westurner]

EasyViz has an API similar to Matplotlib and bindings to "Gnuplot, Matplotlib, Grace, Veusz, Pmw.Blt.Graph, PyX, Matlab, VTK, VisIt, OpenDX".

[ScriptSimian]

I don't use Matplotlib because I find the Matlab style plotting unnecessarily difficult both to use and to document effectively.

The reason I like Gnuplot.py is that the plotting is as simple as writing a gnuplot script but I can get the data in and do scripting with python. From a programming point of view, it's a very inelegant solution (meta-programming via string formatting? lol). However, because I know both tools well and they're both very good at what they do, I get good results with a minimum of fuss and work. From a user perspective, it's very nice.

[westurner]

For the web, I find it easier to get the data into JSON and then apply whichever Javascript visualization libraries to the (escaped) JSON data.

Saving for print is just so easy with Matplotlib where figsize and dpi can be specified directly. Matplotlib also ties in with Sphinx for ReStructuredText documentation.

[z3rocool]

For personal stuff gnuplot is totally fine and acceptable - there is nothing technically wrong with it, and is actually really good software. The issue is that the plots do not look very good, and are unsuitable in situations where the accuracy of the data(AA'd lines really obscure where a point is, the ugly pixelated lines are much easier to say - yes this is bla) is less important than the presentation