# Teradata Ordinal Encoding Suite

> Ordinal encoding for ordered categorical variables

- Skill: `teradata-labs/teradata-ordinal-encoding-suite` (Agent Skill, multi-file: 11 files)
- Install (CLI): `npx skillmds@latest add teradata-labs/teradata-ordinal-encoding-suite`
- Raw SKILL.md: https://api.skillmd.com/api/skills/teradata-labs/teradata-ordinal-encoding-suite/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: teradata-labs (https://skillmd.com/u/teradata-labs)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/teradata-labs/teradata-ordinal-encoding-suite

---


# Teradata Ordinal Encoding Suite

| Property | Value |
|----------|-------|
| **Skill Name** | Teradata Ordinal Encoding Suite |
| **Description** | Ordinal encoding for ordered categorical variables |
| **Category** | Feature Engineering |
| **Primary Function** | TD_OrdinalEncodingFit |
| **Framework** | SQLE |

## Core Capabilities

- Automated table structure analysis via DBC.ColumnsV
- Dynamic SQL generation for TD_OrdinalEncodingFit
- Complete workflow from data preparation to results interpretation
- Data quality validation and preprocessing guidance
- Parameter optimization and tuning

## Key Parameters

- **TargetColumn**: Categorical column to encode
- **Approach**: 'LIST' (manual order) or 'AUTO' (alphabetical)
- **Categories**: Ordered list of category values (for LIST approach)
- **OrdinalValues**: Corresponding integer values
- **Accumulate**: Columns to keep in output (Transform)

## Use Cases

1. Encoding ordered categories (low/medium/high)
2. Feature engineering for ML models
3. Survey response encoding
4. Education level or rating encoding

## Example Usage

```sql
-- TD_OrdinalEncodingFit execution
SELECT * FROM TD_OrdinalEncodingFit (
    ON {USER_DATABASE}.{USER_TABLE} AS InputTable
    USING
    TargetColumn ('{CATEGORICAL_COLUMN}')
    Approach ('LIST')                  -- 'LIST' (manual) or 'AUTO' (alphabetical)
    Categories ('{CAT_1}','{CAT_2}','{CAT_3}')
    OrdinalValues (1, 2, 3)
) AS dt;
```

## Scripts Included

### Core Analytics Scripts
- **`table_analysis.sql`**: Automatic table structure discovery
- **`preprocessing.sql`**: Data preparation and feature engineering
- **`model_training.sql`**: TD_OrdinalEncodingFit execution
- **`evaluation.sql`**: Results analysis and metrics
- **`complete_workflow_template.sql`**: End-to-end workflow

### Utility Scripts
- **`data_quality_checks.sql`**: Comprehensive data validation
- **`parameter_tuning.sql`**: Parameter optimization
- **`diagnostic_queries.sql`**: Results diagnostics and interpretation

## Best Practices

- Always run table_analysis.sql first to understand your data structure
- Validate data quality before executing the analytical function
- Use parameter_tuning.sql to find optimal configuration
- Review diagnostic_queries.sql output for model/results validation

## Limitations

- Requires Teradata Vantage 17.20+ with ClearScape Analytics
- Input data must meet function-specific requirements
- Results depend on data quality and parameter configuration

*Teradata Ordinal Encoding Suite - ClearScape Analytics skill for Teradata Vantage*