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Analyzing Election and Polling Data in R

Learn R for data science by wrangling, visualizing, and modeling political data like polls and election results.

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4 Hours15 Videos55 Exercises6,191 Learners
4650 XP

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Course Description

This is an introductory course to the R programming language as applied in the context of political data analysis. In this course students learn how to wrangle, visualize, and model data with R by applying data science techniques to real-world political data such as public opinion polling and election results. The tools that you'll use in this course, from the dplyr, ggplot2, and choroplethr packages, among others, are staples of data science and can be used to analyze almost any dataset you get your hands on. Students will learn how to mutate columns and filter datasets, graph points and lines on charts, make maps, and create models to understand relationships between variables and predict the future. This course is suitable for anyone who already has downloaded R and knows the basics, like how to install packages.

  1. 1

    Presidential Job Approval Polls


    Chapter one uses a dataset of job approval polling for US presidents since Harry Truman to introduce you to data wrangling and visualization in the tidyverse.

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    50 xp
    Selecting columns of data
    100 xp
    Filtering rows of data
    100 xp
    Averaging job approval by president
    50 xp
    Averaging approval ratings by president
    100 xp
    Averaging a column
    100 xp
    Visualizing Trump's approval over time
    50 xp
    Averaging president Trump's approval by month
    100 xp
    Calculating a rolling average of polls
    100 xp
    Visualizing Donald Trump's approval polls
    100 xp
    Bonus: Visualizing every president's approval
    100 xp
  2. 4

    Predicting the Future of Politics

    In this ensemble of applied statistics and data analysis, you will wrangle, visualize, and model polling and prediction data for two sets of very important US elections: the 2018 House midterms and 2020 presidential election.

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Brexit PollsBrexit ResultsGallup Approval PollsGeneric BallotUS Pres 2016 by County


David CamposChester IsmayShon Inouye
G Elliott Morris Headshot

G Elliott Morris

Data Journalist

Elliott Morris is a data journalist who uses applied statistics and data science techniques with R to analyze, visualize, and model political (and other) data. Before he wrote articles and code professionally, he studied government, history, and computer science at the University of Texas at Austin. He shares his work frequently on Twitter (@gelliottmorris) and writes about data in politics at his blog, The Crosstab.
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I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

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Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

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Harvard Business School

DataCamp is by far my favorite website to learn from.

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Decision Science Analytics, USAA