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Electoral Votes 2016

Posted 6 years ago
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If you want to do some programming with US electoral votes, you will need to start with the basic state-to-electoral vote data.

In this cloud notebook, I show how you can import this data and work with it: http://www.wolframcloud.com/objects/jfklein/elections2016/electoral-votes-2016.nb

The basic data can be imported here:

data = Import[
  "http://www.infoplease.com/us/government/electoral-college-votes-state-elections.html", "Data"]

The data includes some headers and other things, so I use Position to find a state name, tweak the position to include all the states data, and then turn it into a list of Rules:

$electoralVotes = Rule @@@ Extract[data, Most[Most[First[Position[data, "Alabama"]]]]]

The results should look like this:

{"Alabama" -> 9, "Alaska" -> 3, "Arizona" -> 11, "Arkansas" -> 6,
"California" -> 55, "Colorado" -> 9, "Connecticut" -> 7, "Delaware" -> 3, "District of Columbia" -> 3, "Florida" -> 29, "Georgia" -> 16, "Hawaii" -> 4, "Idaho" -> 4, "Illinois" -> 20, "Indiana" -> 11, "Iowa" -> 6, "Kansas" -> 6, "Kentucky" -> 8, "Louisiana" -> 8, "Maine" -> 4, "Maryland" -> 10, "Massachusetts" -> 11, "Michigan" -> 16, "Minnesota" -> 10, "Mississippi" -> 6, "Missouri" -> 10, "Montana" -> 3, "Nebraska" -> 5, "Nevada" -> 6, "New Hampshire" -> 4, "New Jersey" -> 14, "New Mexico" -> 5, "New York" -> 29, "North Carolina" -> 15, "North Dakota" -> 3, "Ohio" -> 18, "Oklahoma" -> 7, "Oregon" -> 7, "Pennsylvania" -> 20, "Rhode Island" -> 4, "South Carolina" -> 9, "South Dakota" -> 3, "Tennessee" -> 11, "Texas" -> 38, "Utah" -> 6, "Vermont" -> 3, "Virginia" -> 13, "Washington" -> 12, "West Virginia" -> 5, "Wisconsin" -> 10, "Wyoming" -> 3}

You can load this list of rules into your own session:

CloudGet[CloudObject["https://www.wolframcloud.com/objects/jfklein/elections-2016/electoral-votes.m"]]

Once you have this basic data, you can do interesting things with it. This visualizes the states with their electoral vote weight:

sortedevotes = SortBy[evotes, Last];
BarChart[Values[sortedevotes], BarOrigin -> Left, ChartLabels -> Keys[sortedevotes], 
  PlotLabel -> "Electoral Votes by State", ImageSize -> 1024]

Bar chart of electoral votes by state

We can also calculate how to win the election with the smallest number of states, which is the collection of the first of the biggest states to add to 270 votes or more.

TableForm[biggestStatesTo270 = TakeWhile[Reverse[sortedevotes], 
    Total[Drop[Values[sortedevotes], 
            First@FirstPosition[sortedevotes, #] - 1]] <= 270 &]]

This shows you can win the presidency by converting just 11 of the largest states:

California -> 55
Texas -> 38
New York -> 29 
Florida -> 29 
Pennsylvania->20 
Illinois->20 
Ohio->18 
Michigan->16 
Georgia->16 
North Carolina->15 
New Jersey->14
POSTED BY: Joel Klein
6 Replies

Nice post, Joel!

Why don't you try to turn those strings into entities and do some maps, or normalize by population? I think it would be interesting to see whether those states account for more or less than half of the population of the US. I recall reading somewhere that Californians were the ones whose vote actually counted the least.

POSTED BY: Carlo Barbieri
Posted 6 years ago

Yep, I have some other material where states are dealt with as entities. Those are all good suggestions for thing to study based on this.

The types of directions I was thinking for this were supporting what-if scenarios for battleground states, projections, etc.

POSTED BY: Joel Klein

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POSTED BY: Moderation Team

Here is a slightly cleaner import and an image collage using Entity.

data = Import[
"http://www.infoplease.com/us/government/electoral-college-votes-state-elections.html", "Data"];
as = Association[Rule @@@ Cases[data, {_String, _Integer}, {5}]]; 

With[{entities = 
       KeyMap[Interpreter["AdministrativeDivision"], as]}, 
     ImageCollage[
      KeyMap[AssociationMap[#["Flag"] &, Keys[entities]][#] &, entities], 
      ImagePadding -> 2, Background -> GrayLevel[.8]]
     ]

enter image description here

POSTED BY: Bob Sandheinrich
KeyMap[Interpreter["AdministrativeDivision"], as]

This is really inefficient, because you'd be interpreting things serially.

AssociationThread[Interpreter["AdministrariveDivision"][Keys[as]], Values[as]]

is probably a bit less elegant, but can be as much as 50 times faster.

POSTED BY: Carlo Barbieri

Voter Power Rankings:

rankings=With[{entities=KeyMap[Interpreter["AdministrativeDivision"],as]},Reverse@Dataset@Sort@Association[KeyValueMap[#1->(N@#2/#1["Population"])&,entities]]
];
rankings[{1;;5,-5;;-1}]

enter image description here

POSTED BY: Bob Sandheinrich
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