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Data Services Class Descriptions

Information, materials, and schedules for all currently offered Data Services classes.

This session covers the basics of cleaning and managing data in R as well as working with strings, dates, and writing your own functions.

Software:	Computer workstations with R and RStudio installed are available for in-person tutorials in Bobst 617. For remote tutorials, while some patrons decide to approach tutorials as a demonstration of the software, other patrons approach tutorials with a more “hands-on” approach and wish to interact with the software during the tutorial. If the latter is the case, we recommend referencing our supported software page for additional information on accessing/downloading the software prior to the tutorial.
Duration:	120 min
Room description:	Some tutorials are held remotely and require NYU sign on to access, while others are held in person, without a remote component. Please note the correct modality and location of the tutorial when registering
Prerequisites:	Basic computer literacy, understanding files and folders Ability to loading data into R from a .csv Understanding of the names and uses of different object types in R
Skills Taught / Learning Outcomes:	Extracting, generating, and modifying strings Extracting dates from strings and producing dates in a desired format Subsetting data sets Merging two data sets Converting panel data from long to wide format and vice versa Producing for loops and using R’s apply functions Writing your own functions Conditional statements Basic tidyverse functions
Class Materials:	Datasets Syntax.html Syntax.Rmd
Related Classes:	Data Visualization with Tableau Data Cleaning Using OpenRefine Introduction to Research Data Management Introduction to Python Reproducible Workflows in R
Additional Training Materials:	guides.nyu.edu/r
Feedback:	bit.ly/feedbackds

Upcoming sessions for this tutorial