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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: R, RStudio
Duration: 120 min

Room description:

During the Fall 2021 semester, 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:
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