[elsherbini]

plotly is a fantastic tool for plotting. It has a python API [0], but also works from R, matlab, and Julia. It also has support for pandas dataframes and jupyter notebook[1], which is by far the fastest way I've found to make attractive plots. plotlyjs[2] is a fantastic wrapper around d3. So I can go all the way from plotting something quickly from a dataframe to building a totally custom chart.

[0] https://plot.ly/python/

[1] https://plot.ly/ipython-notebooks/cufflinks/

[2] https://plot.ly/javascript/

[qacek]

I like plotly as well but I couldn't stand the python api nor cufflinks for that matter so I created my own wrapper. It's not fully featured but it handles 90% of the cases I want.

https://github.com/jwkvam/plotlywrapper

[elsherbini]

very nice. I like that it each chart method returns the figure, so if it is needed to do something you didn't implement the figure is available to edit.

[qacek]

Thanks, I am happy to accept PRs that expose more functionality.

[ced]

How does it compare with Bokeh?

[elsherbini]

I prefer the aesthetic of the defaults in plotly over Bokeh. Also, for most of my tasks I can simply use dataframe.iplot() using the library from [1] above, and I value that simplicity. Lastly, I prefer that plotly is built on top of d3js so I have access to that api if I want to do anything crazy, whereas Bokeh reinvented the wheel a bit with BokehJS.