Ask HN: What data visualisation tools do data scientists and developers use?

Re:Ask HN: What data visualisation tools do data scientists ... by elcritch on Thursday July 23, 2015 @04:07PM (#9938168)

The default themes / colors in matplotlib leaves something to be desired. I'd recommend checking into [seaborn(http://stanford.edu/~mwaskom/software/seaborn/) for setting nice default colors and handling many types of statistical data plots. It reduces a lot of the boiler plate.

For visualizations that need to be shared IPython notebooks are great and work with Julia & R as well. The @interact widgets are fantastic for exploring data. Unfortunately interactive notebooks are difficult to post on a static website.

To answer the OP's other questions:

For that, I've been moving to a mix of html5/javascript/d3. While it's still a new-ish mix compared to matplotlib, there is something about being able to save all the data and computations to an html file which anyone with a decent browser can open and interact with is fantastic. I utilize this method to store my protocol records for experimental tests. One file can contain pretty self-describing data along with javascript code to nicely present it.

[ Parent | on HN ]

Re:Ask HN: What data visualisation tools do data scientists ... by bluusteel on Thursday July 23, 2015 @09:47PM (#9939671)

I don't think I realized how important default colors/styles are for visualization software until using seaborn. Quickly producing sensible plots in terms of aesthetics should not require 10+ lines of extra code. Fortunately, it looks like the matplotlib folks are looking to change default colors/styles with 2.0 [1].

[1]http://matplotlib.org/style_changes.html

[ Parent | on HN ]