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Tag Archives: idv
One more IDV in Python approach
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Its 2018, how to IDV in Python?
I’ve got a fun little viz that I need to demo for Important People (IP) in early March [editor’s note: still not done… that deadline was highly optimistic!]. How to do it?
In Python? Sure. In a Jupyter notebook? Maybe. With Matplotlib? Probably not… at least I better have a look at the state of the alternatives.
Did I mention that it is essential for this viz to be *interactive*? It needs to allow the Important People to explore the predictions of some ML model, or at least allow me to explore them while they call out how to explore.
Years ago, I attempted to designate a particular plot the “hello, world” of data viz. Remember that? I think we should extend it to a hello world of interactive data viz. Maybe just choosing the number of digits is enough. Or should it follow the visual information seeking mantra? But “hello, world” cannot be too complicated.
yhat?
Altair
https://altair-viz.github.io
https://github.com/altair-viz/altair_widgets/blob/master/examples/Iris.ipynb
http://pbpython.com/altair-intro.html
Bokeh
https://bokeh.pydata.org/en/latest/docs/gallery.html#gallery
https://www.analyticsvidhya.com/blog/2015/08/interactive-data-visualization-library-python-bokeh/
Click to access Python_Bokeh_Cheat_Sheet.pdf
https://www.datacamp.com/courses/interactive-data-visualization-with-bokeh/
https://www.datacamp.com/community/blog/bokeh-cheat-sheet-python
https://demo.bokehplots.com/apps/movies
A Dramatic Tour through Python’s Data Visualization Landscape (including ggplot and Altair)
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Follow-up to the classroom-worthy visual analytics example
Did you have a chance to see the sum-to-fifteen game I learned about last week?
Here is an animated version of playing it:
And here is what it looks like if you arrange the numbers in just the right 2d grid:
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A classroom-worthy example of the power of visual analytics
I started reading an “economics of diversity” book recently, and stumbled across a great example of the power of visual analytics (included early in the book to demonstrate the value of diverse representations):
This game is hard, right? I mean I have to think about it to figure out a good move. But if you think of it visually, the right way, it is not hard. I’ll leave it as a mystery for now, and say that I can imagine a classroom exercise on this when I next teach interactive data visualization again.
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Visualizing Uncertainty
Click to access paper_BELIV_evaluating_uncertainty_vis.pdf
Click to access HoekstraEtAlPBR.pdf
Click to access uncertain-bus-chi2016.pdf
Click to access MacEachren_Visualizing_98.pdf
Click to access MacEachren_IEEE_TVCG_PrePub_2012_reduced_res.pdf
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6654171
Click to access MacEachren_IEEE_TVCG_PrePub_2012_reduced_res.pdf
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New words of wisdom from S Few
The Visual Perception of Variation in Data Displays
Click to access the_visual_perception_of_variation.pdf
(well, it was new when I started this post)
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Javascript Things of Note
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To read: EnsembleMatrix paper
EnsembleMatrix: Interactive Visualization to Support Machine Learning with Multiple Classifiers http://research.microsoft.com/en-us/um/redmond/groups/cue/publications/CHI2009-EnsembleMatrix.pdf
I want one
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Filed under dataviz, machine learning
IDV in Python: Interactive Legend in MPLD3
We got a nice pull request for mpld3 recently, interactive legends. Another chance for me to use my new GIF animation recorder: https://github.com/jakevdp/mpld3/pull/299#issuecomment-110434953
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Unhide a toolbar in MPLD3
Did you ever want to know how to unhide the toolbar in MPLD3? Here is how: http://stackoverflow.com/questions/29976625/unhide-toolbar-in-mpld3
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Healthy Algorithms 