Data Cleaning and Tidying

How to Clean and Tidy Data

• How to Clean and Tidy Data
• Recoding
• Delete Poor-Quality Cases
• Rebasing Data

Widening, Stacking, and Other Ways of Reshaping/Restructuring Data Files

• Reshaping a Data Set: Widening, Stacking, Aggregating, and Merging Data FIles
• Aggregating Data
• Merging Data Files and Data Tables
• Stacking Data

Dealing with Missing Values

• Missing Values in Cluster Analysis and Latent Class Analysis
• How Missing Values are Addressed in Statistical Analysis
• Analysis Methods That Automatically Address Missing Values
• Imputing Missing Data
• Filtering Missing Values from Analyses

Creating New Variables

• How to Compute Binary Variables Using JavaScript
• Creating New Variables by Duplicating and Modifying Variable Sets
• Creating Variables Using In-Built Options
• Creating New Variables by Creating Filters
• Creating New Variables by Writing Code

Transforming Numeric Variables

• Converting Numeric Variables to Categorical Variables
• Midpoint Recoding
• Reverse Coding
• Aligning Values With Labels
• Capping

Transforming Categorical Variables

• Merging Categories
• Converting Categorical Variables to Numeric Variables
• Probability Coding Intentions Data
• Calculating NPS and Other Difference Between Percentages Variables
• Converting Categorical Variables to Binary Variables
• Dummy Variables