Add drop down filtering

[dmarx]

• https://plot.ly/python/dropdowns/
• https://plot.ly/python/custom-buttons/
• https://plot.ly/python/reference/#layout-updatemenus

Filters:

• Stories about russia vs. misc news
• highlight megathread
• show/hide regular submissions
• color by is_russia vs "g_score > g_num_comments"
• gallup approvals/disapprovals/% more disapprove

Complexities:

• I think to get this to work for plotly, I need a separate button for each combination of variables, and each variable will be a series (and set of residuals) that gets shown or hidden

Button Description	is_russia	is_megathread	g_col
button0	0	0	0
button1	0	1	0
button2	1	0	0
button3	1	1	0
button4	0	0	1
button5	0	1	1
button6	1	0	1
button7	1	1	1

This is uglay, but from plotly's "custom button" docs, it appears to be their recommended practice. Reference the "all" and "both" options in the "relayout" and "update" button demos.

• If we're playing with the gallup data, we'll probably need to reformat the axes every time we change the series

[dmarx]

This looks like a way more versatile and customizable solution:

• https://plot.ly/python/slider-widget/

Related resources;

• https://github.com/jupyter-widgets/ipywidgets
• https://plot.ly/python/ipython-widgets/
• https://moderndata.plot.ly/widgets-in-ipython-notebook-and-plotly/

[dmarx]

GraphWidget is designed for hosted plotly graphs, not offline mode. Here's a demo of a possible solution for offline mode:

• http://nbviewer.jupyter.org/github/yankev/test/blob/master/plotlywidget_working2.ipynb

NB: This solution completely redraws the chart rather than updating it. There's probably a better way.

[dmarx]

This will work locally but according to this, widgets won't display in nbviewer, which makes sense: rebuilding the chart each time this way requires running a bespoke python function. Obviously I need a running kernel for this to work. Might still be fun to play with and worth implementing as an experiment and learning experience, but not the way to go if my goal is build something random people online can use simply.

[dmarx]

This hasn't been updated in two years, but might be worth checking out: https://github.com/plotly/postMessage-API

[dmarx]

I thought the control elements I had been playing with were the newly deployed features I had read about, but it looks like that's a new dashboarding package called "dash", which I may need to install separately:

• https://plot.ly/dash/
• https://github.com/plotly/dash
• https://plot.ly/python/ipython-notebook-tutorial/#publishing-dash-apps

I have a feeling if widgets won't work on nbviewer, neither will Dash. Uses Flask and socketio in the backend... not super optimistic. I need the ability to embed JSON and/or manipulate the d3 directly.