R for Data Science: Data Analysis in Practice (Part 2)

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In 1.5 focused hours, you’ll learn:

How to wrangle data using tidyverse — select, filter, mutate, arrange
How to group and summarize datasets with dplyr
How to clean messy string data with stringr
How to visualize results with ggplot2

This is a continuation of our Oct 7 R workshop — we’ll finish the exercises we started and push further into hands-on data analysis. No prior R experience required. Bring your laptop with R and RStudio installed (both free at r-project.org and posit.co).

If you anticipate a need for disability-related accommodations or auxiliary aids to attend or participate, please contact The Fleishman Center for Career and Professional Development at careers@binghamton.edu. We ask that you provide us with at least 3-5 days of advance notice regarding your equal access needs.

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