Data wrangling in R

As social scientists, we spend a considerable amount of our time cleaning, selecting, and managing our data; yet, most of us never received formal instruction on such methods and hence have developed idiosyncratic ways to wrangle data. These methods are often not sharable, not reproducible, and —I will speak for myself here — are not practices that we are particularly proud of.

In this office hour, I will demonstrate how a set of tools within R called the Tidyverse can streamline your data management by making it transparent, shareable and computationally reproducible. These tools are widely used in the so-called Data Science world, and are intuitive and easy to learn. The last part of the hour will include a hands-on exercise in which participants will transform a raw and noisy data file, and will select the relevant information to make it suitable for analyses and tables. This exercise in the last part of the meeting will be delivered via the Rstudio cloud platform through this link: https://rstudio.cloud/project/1122015.

How to access: Open Office Hours are delivered using Zoom. Meetings are password protected, so participants will need to enter a password in order to join an Open Office Hour. Meeting rooms and passwords will be sent by email to those who have provided contact information for that purpose.

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