Data explorer
Data explorer
Cross-tabulate any two fields, check what is missing, and summarise groups. Every cell links to the records behind it.
Agency1
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Agency: DOE · Department of EnergyAI type: Classical / predictive ML
Agency × Development stage
105 recordsMissing-data analysis
Core fields, current filter| Field | Filled | Missing | Filled % |
|---|
| Stage | 105 | 0 | 100% |
| High-impact designation | 105 | 0 | 100% |
| Topic area | 105 | 0 | 100% |
| AI classification | 105 | 0 | 100% |
| Problem | 105 | 0 | 100% |
| Benefits | 105 | 0 | 100% |
| Outputs | 105 | 0 | 100% |
| Sourcing | 41 | 64 | 39% |
| Start date | 40 | 65 | 38% |
| ATO | 45 | 60 | 43% |
| PII | 45 | 60 | 43% |
| Custom code | 45 | 60 | 43% |
Descriptive statistics
Current filter| Records | 105 |
| Agencies | 1 |
| Records per agency: median | 105 |
| Records per agency: largest | 105 |
| Deployed share | 20.0% |
| High-impact share (of designated) | 6.7% |
| Mean core-field completeness | 75% |
| Records with a parseable start date | 38.1% |
Grouped summary by agency
Shares use each agency's own record count| Agency | Records | Deployed % | Pilot % | High-impact | Generative % | In-house (of reported) | Completeness |
|---|
| DOE | 105 | 20% | 12% | 7 | 0% | 66% | 75% |