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  3. Case Study: Exploratory Data Analysis in R
  • 1

    Data cleaning and summarizing with dplyr

    Free

    The best way to learn data wrangling skills is to apply them to a specific case study. Here you'll learn how to clean and filter the United Nations voting dataset using the dplyr package, and how to summarize it into smaller, interpretable units.

  • 2

    Data visualization with ggplot2

    Once you've cleaned and summarized data, you'll want to visualize them to understand trends and extract insights. Here you'll use the ggplot2 package to explore trends in United Nations voting within each country over time.

  • 3

    Tidy modeling with broom

    While visualization helps you understand one country at a time, statistical modeling lets you quantify trends across many countries and interpret them together. Here you'll learn to use the tidyr, purrr, and broom packages to fit linear models to each country, and understand and compare their outputs.

  • 4

    Joining and tidying

    In this chapter, you'll learn to combine multiple related datasets, such as incorporating information about each resolution's topic into your vote analysis. You'll also learn how to turn untidy data into tidy data, and see how tidy data can guide your exploration of topics and countries over time.

Initializing

Exercise

Adding a country column

The country codes in the ccode column are what's called Correlates of War codes. This isn't ideal for an analysis, since you'd like to work with recognizable country names.

You can use the countrycode package to translate. For example:

library(countrycode)

# Translate the country code 2
> countrycode(2, "cown", "country.name")
[1] "United States"

# Translate multiple country codes
> countrycode(c(2, 20, 40), "cown", "country.name")
[1] "United States" "Canada"        "Cuba"

Instructions

100 XP
  • Load the countrycode package.
  • Convert the country code 100 to its country name.
  • Add a new country column in your mutate() statement containing country names, using the countrycode() function to translate from the ccode column. Save the result to votes_processed.