paid course

Importing & Cleaning Data in R: Case Studies

  • 4 hours
  • 0 Videos
  • 35 Exercises
  • 7,249 Participants
  • 3500 XP
Nick Carchedi
Nick Carchedi

Director of Content at DataCamp

Prior to leading the Content team at DataCamp, Nick earned his master's degree at Johns Hopkins Biostatistics and worked as a data scientist for McKinsey. Nick's passion for teaching data science began in graduate school, where he was heavily involved in tutoring fellow students, developing the Johns Hopkins Data Science Specialization, and building the swirl R package.

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Collaborator(s)
  • Jim Looney

    Jim Looney

  • Tom Jeon

    Tom Jeon

Course Description

Running exciting analyses on interesting datasets is the dream of every data scientist. But first, some importing and cleaning must be done. In this series of four case studies, you'll revisit key concepts from our courses on importing and cleaning data in R.

  1. 1

    Ticket Sales Data

    Free

    Hone your skills by importing and cleaning some wonderfully messy online ticket sales data.

  2. MBTA Ridership Data

    Boston's public transit system needs your help! The T wants to do some data analysis and you've been asked to clean their ridership data.

  3. World Food Facts

    We all know that you are what you eat, so what exactly are you? In this chapter, you'll import and clean some data about food products from around the world.

  4. School Attendance Data

    Use all of the tools you've learned to import and clean a gnarly dataset containing information on average school attendance in the US.