Module: Data Pivoting
(Conditioning)
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| Lesson Objective | Learn how to pivot data to reformat from a tall/skinny to a short/wide organization, aggregate replicate measures, and other data conditioning methods |
| Section | Description |
| Data Pivoting | A discussion of the utility of data pivoting and aggregation. |
| Tall/Skinny => Short/Wide | A definition and example of what it means to "pivot data." |
| Pivoting the Current DecisionSite Data Set | How to pivot data, including details for the following pivot terms: Identity, Category, Values, and Other columns. |
| Other Data Pivoting Options | How to access other data conditioning options. |
| Tall/Skinny => Short/Wide (Alt 1) vs. (Alt 2) | A discussion of the difference between Tall/Skinny => Short/Wide (Alt 1) and (Alt 2). |
| Table Rotation Without Aggregation | How to achieve table reformatting without aggregation, and consideration of the resulting data column titles. |
| Using More than One Column to Define an Identity | An example which requires two values for unique identity. |
| Using More than One Column to Define a Category | An example which requires two values for unique category. |
| Concatenation of Non-unique String Values | The result of pivoting multiple text values is a comma-separated string. |
| Case Normalizer | A discussion of the Case Normalizer data conditioning tool and how it serves to treat string values the same, independent of case. |
| New Column from Expression | A discussion of how the New Column from Expression data conditioning tool allows you to perform calculations upon import. |
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