PhD+ Data Science Essentials in R: Data Preparation

Office of Graduate & Postdoctoral Affairs

The <A HREF="https://www.library.virginia.edu/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">UVA Library’s</A> <A HREF="https://data.library.virginia.edu/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Research Data Services Team</A> is partnering with UVA’s <A HREF="http://phdplus.virginia.edu/" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">PhD Plus program</A> to pilot a new module – Data Science Essentials in R – a six-session series to build data analysis, wrangling, and visualization skills.
Data Preparation/Tidy Data in R - Before analyzing data, we spend considerable effort wrangling the data into an analyzable form – creating and recoding variables, merging data sets, filtering and aggregating data, reshaping and more. In this workshop, we’ll learn about data preparation using dplyr, a library defining a grammar of data manipulaiton, and tidyr, a library for reshaping and tidying data. We’ll also cover working with data types like factors and dates and using conditional logic.

PhD+ Data Science Essentials in R: Data Preparation

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PhD+ Data Science Essentials in R: Data Preparation

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