Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Harvard University

Data Science: Wrangling

Harvard University via edX


In this course, part of our Professional Certificate Program in Data Science,we cover several standard steps of the data wrangling process like importing data into R, tidying data, string processing, HTML parsing, working with dates and times, and text mining. Rarely are all these wrangling steps necessary in a single analysis, but a data scientist will likely face them all at some point.

Very rarely is data easily accessible in a data science project. It's more likely for the data to be in a file, a database, or extracted from documents such as web pages, tweets, or PDFs. In these cases, the first step is to import the data into R and tidy the data, using the tidyverse package. The steps that convert data from its raw form to the tidy form is called data wrangling.

This process is a critical step for any data scientist. Knowing how to wrangle and clean data will enable you to make critical insights that would otherwise be hidden.

Taught by

Rafael Irizarry


4.5 rating, based on 2 Class Central reviews

4.3 rating at edX based on 18 ratings

Start your review of Data Science: Wrangling

  • Profile image for Luiz Cunha
    Luiz Cunha
    The topic is quite dry.
    But this Course does well in teaching concisely the main concepts and gives good practical examples and exercises related to this rather tidious subject
  • Anonymous
    very good *intro* to the subject.
    very clear to understand, and made me dig deeper on my own :)
    notice that this is an entry-level to the subject

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.