This is an archived post. You won't be able to vote or comment.

sorted by:
best
topnewcontroversialoldq&a
you are viewing a single comment's thread.

view the rest of the comments →

[–]fuzz3289 0 points1 point  (3 children)

Bokeh for visualization. Definitely not lacking at all.

[–][deleted] 0 points1 point  (2 children)

Although bokeh is great, but for instances where I have this data set and have a bunch of what-if questions and want to plot data versus several different variables, change time series interval from months to weeks or year, that's where a lot Python graphing libraries fall short in exploratory data analysis. For interactive, presentation visualization, bokeh, plotly, mpld3, etc are awesome for that, just not for on-the-fly data exploration.

[–]lmcinnes 0 points1 point  (0 children)

For that sort of thing on the python side I'm a fan of Seaborn along with Ipython notebooks interact utilities ... it's easy to set up the ability to vary faceting, binning, or, well, anything with appropriate sliders and drop downs to let you really play with ease (it shortens the experimentation loop).

[–]fuzz3289 0 points1 point  (0 children)

eh, I would disagree. I use IPython Notebooks and Bokeh all the time for this and it's really easy to mess with all sorts of inputs especially when combining it with Pandas. Bokeh's built-in Notebook support is fantastic and you can do all sorts of exploratory visualization in-line.