Tidy Data Principles: General Data Structure Best Practices | UTA Libraries
This video covers the concept of tidy data, the optimal format for data use in various tools (like SPSS, R, and Tableau). It looks quite different from the sorts of formats you may typically come across when using spreadsheet software like Excel. So, if you are having issues with restructuring your dataset for analysis or visualization, this workshop is for you!
For more information, visit https://libraries.uta.edu/research/sc...
Copyright: CC-BY 4.0
Correction 1: In the example dataset, the first few rows of the "Race/Ethnicity" column in the tidy version should say "Total" instead of "American Indian/Alaska Native."
Correction 2: At 15:43, "Common Functions" should say "Common Commands."
Timestamps:
0:00 - Video Introduction
0:48 - Common Data Terms
3:52 - About Tidy Data Structure
4:42 - Example of Going from Messy to Tidy
6:23 - 5 Common Issues with Datasets' Structure
7:39 - Issue 1: Column Headers Are Values Not Variable Names
8:22 - Issue 2: Multiple Variables Are Stored In One Column
9:10 - Issue 3: Variables Are Stored in Both Rows and Columns
10:21 - Issue 4: Multiple Types of Observational Units Are Stored in the Same Table
13:25 - Issue 5: A Single Observational Unit is Stored in Multiple Tables
14:41 - Tools for Data Restructuring
15:25 - R Packages and Commands for Data Restructuring
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