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Election tRends: An interactive US election tracker (using Shiny and Plotly)

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Guest post by Jonathan Sidi

Introduction

The US primaries are coming on fast with almost 120 days left until the conventions. After building a shinyapp for the Israeli Elections I decided to update features in the app and tried out plotly in the shiny framework.

As a casual voter, trying to gauge the true temperature of the political landscape from the overwhelming abundance of polling is a heavy task. Polling data is continuously published during the state primaries and the variety of pollsters makes it hard to keep track what is going on. The app self updates using data published publicly by realclearpolitics.com.

The app keeps track of polling trends and delegate count daily for you. You create a personal analysis from the granular level data all the way to distributions using interactive ggplot2 and plotly graphs and check out the general elections polling to peak into the near future.

The app can be accessed through a couple of places. I set up an AWS instance to host the app for realtime use and there is the Github repository that is the maintained home of the app that is meant for the R community that can host shiny locally.

Running the App through Github

(github repo: yonicd/Elections)

#changing locale to run on Windows
if (Sys.info()[1] == "Windows") Sys.setlocale("LC_TIME","C") 
 
#check to see if libraries need to be installed
libs=c("shiny","shinyAce","plotly","ggplot2","rvest","reshape2","zoo","stringr","scales","plyr","dplyr")
x=sapply(libs,function(x)if(!require(x,character.only = T)) install.packages(x));rm(x,libs)
 
#run App
shiny::runGitHub("yonicd/Elections",subdir="USA2016/shiny")
 
#reset to original locale on Windows
if (Sys.info()[1] == "Windows") Sys.setlocale("LC_ALL")

Application Layout:

(see next section for details)

  1. Current Polling
  2. Election Analyis
  3. General Elections
  4. Polling Database

Usage Instructions:

Current Polling

Election Analysis

The user can choose to filter in the plots States, Parties, Candidates, Pollsters. Next there is a slider to choose the days before the conventions you want to view in the plot. This was used instead of a calendar to make a uniform timeline that is cleaner than arbitrary dates. Since there are a lot of states left and no one keeps track of which ones are left an extra filter was added to keep just the states with open primaries.

The new feature added is the option to go fully interactive and try out plotly!. Its integration with ggplot is great and new features are being added all the time to the package.

The base graphics are ggplot thus the options above the graph give the user control on nearly all the options to build a plot. The user can choose from the following variables: Date, Days Left to Convention, Month, Weekday, Week in Month, Party, Candidate, State, Pollster, Results, Final Primary Result, Pollster Error, Sample Type (Registerd/Likely Voter), Sample Size. There is an extra column in the Polling Database tab that gives the source URL of the poll that was conducted for anyone who wants to dig deeper in the data.

To define the following plot attributes:

Plot Type Axes Grouping Plot Facets
Point X axis variable Split Y by colors using a different variable Row Facet
Bar Discrete/Continuous Column Facet
Line Rotation of X tick labels
Step Y axis variable
Boxplot
Density

An example of the distribution of polling results in the open primaries over the last two months:

Zooming in to this trend we can see the state level polling

An analysis showing the convergence of polling errors to Sanders and Clinton over the Primary season. Initially Sanders was underestimated by the pollsters and over time the public sentiment has shifted. Currently the pollsters have captured the public sentiment to the primary outcomes. This can be seen as a ceiling to the Sanders campaign:

#new layer
p+geom_smooth(aes(x=DaysLeft,y=Results,fill=Candidate))+
scale_x_reverse()+scale_fill_discrete(name="Candidate")
#new layer
p=p+geom_smooth(aes(x=DaysLeft,y=Results,fill=Candidate))+
scale_x_reverse()+scale_fill_discrete(name="Candidate")

remove_geom(p,"point") #leaving only the trend on the plot

General Elections

Polling Database

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