Plot + Scatter @plotandscatter
Data analysis, UX, & UI. We transform data for human consumption. [email protected] plotandscatter.com Vancouver, BC Joined October 2014-
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@jdanplant @visualisingdata Thanks, Dan. So glad to hear it — and the feeling’s mutual! And thanks again, Andy.
ICYMI last week, our latest viz: How blue is Alberta? An interactive history of regionality in Canadian elections plotandscatter.com/canadian-elect…
Don’t know who wrote it, but it’s a nice overview — and the linked visualizations are worth checking out!
Pleasantly surprised that the Canadian government issued this short and sweet dataviz primer. Let’s see if we can find out who wrote it @robroc @chadskelton @nicolaskruchten @stefhaustein @plotandscatter @janezhgw H/t @cjlmiles via @DataVizSociety open.canada.ca/en/data-visual…
This is interesting...
How blue is Alberta? Very! This election result is in no way historically special. Interactively explore regional party support in elections since 1968 with our new visualization: plotandscatter.com/canadian-elect… #cdnpoli #elxn43
@PeterVogel Thanks, Peter! A couple more election-related visualizations in the pipeline…
Not bad for a simple model. Hope to expand on this, including comparing with predictions based on last-available *polling* (as opposed to *actual* results), later in the week.
On a regional basis, the model correctly predicted ridings as follows: Atlantic 25/32 (78%) Quebec 66/78 (85%) Ontario 111/121 (92%) Prairies 25/28 (89%) Alberta 34/34 (100%) British C. 38/42 (90%) Territories 2/3 (67%)
How effective is a regionally-weighted swing model (of the kind used in our app at plotandscatter.com/canada-electio…) at predicting election results? Here are the preliminary findings based on this week’s election.
How blue is Alberta? Very! This election result is in no way historically special. Interactively explore regional party support in elections since 1968 with our new visualization: plotandscatter.com/canadian-elect… #cdnpoli #elxn43
For anyone who wants to work with the preliminary results from last night’s election released by @ElectionsCan_E, the long format can be a little annoying. I put them into wide CSV format: gist.github.com/hangler/0554ce… May have errors: caveat downloader. #cdnpoli #elxn43
(The reason for this is that the regionally-weighted swing model distributes that shift most heavily in areas the Conservatives were already strong in, i.e. AB / SK.)
…(i.e. Liberals at 31.0%), they would only have had ~50% chance of winning a minority. Again, this is assuming a regionally-weighted swing, usual disclaimers apply, etc, etc. But still.
One interesting finding: a swing model (using regional weights from last night) suggests that the Liberal vote was so efficient that even had the Conservatives won 36.5% of the vote *exclusively at the expense of the Liberals*…
New version of the Canadian Election Explorer deployed, now with preliminary Elections Canada results from last night: plotandscatter.com/canada-electio… #cdnpoli #elxn43
For posterity: our simple regionally-weighted election app (plotandscatter.com/canada-electio…), using CBC Poll Tracker regional values, gives L144 • C119 • N42 • BLQ 31 • G2. Only a few hours till we know for sure…
At least with these figures, the number of available two-party coalitions is relatively low, reflecting just how fractured public opinion appears to be. CON + NDP seems statistically likely, but is perhaps politically less so. LIB + NDP only works ~56% of the time.
Lots of talk of minority governments lately! The Insights view, newly added to our tool (plotandscatter.com/canada-electio…), simulates elections and shows statistically likely outcomes. A large variety of possible minority coalitions, given current polling numbers. #cdnpoli #elxn43
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