Real-world datasets for learning data science in R

R comes with a range datasets that can be used when learning the basics or trying out a new approach/package. mtcars and weather` are popular choices.

However, most of the common datasets are “toy” examples. They are great for practising basic techniques, but are useless when it comes to realistically simulating data science tasks.

The dslabs package provides datasets more suited to exploring data science techniques. It includes

• admissions Gender bias among graduate school admissions to UC Berkeley (example of Simpson’s paradox)
• divorce_margarine Divorce rate and margarine consumption data (illustrates spurious causation)
• gapminder Health and income outcomes
• heights Self-reported heights
• murders US gun murders by state for 2010
• na_example Randomly generated count data with missing values
• outlier_example Randomly generated adult male heights (in feet) with outliers
• polls_us_election_2016 Fivethirtyeight 2016 Poll Data
• research_funding_rates Gender bias in research funding in the Netherlands
• rfalling_object Simulate falling object data
• take_poll Models results from taking a poll