Quick Reference
| Field | What it means |
|---|---|
| total_compared | Number of rows in the expected data (calculated from your CSV files) |
| rows_compared | Rows where we found a match in both expected AND extracted data |
| rows_matched | Rows that matched perfectly (found in both, zero value differences) |
| rows_with_differences | Rows found in both datasets but have at least one value mismatch |
| rows_missing | Rows in expected data with no matching row in extracted data |
| rows_extra | Rows in extracted data with no matching row in expected data |
| difference_count | Total number of individual value differences (one row can have multiple) |
Common Questions
What does "rows_missing" mean?
We calculated an expected row from your raw data, but the AI could not find or extract a matching row from the PDF. This typically means:
- The question or segment is missing from the PDF entirely
- The AI failed to extract that particular row
- The row key didn't match (e.g., question text differs slightly)
What does "rows_extra" mean?
The AI extracted a row from the PDF that we didn't expect based on our calculations. This typically means:
- The PDF contains data we didn't calculate (e.g., different time period)
- The AI misread something as a data row
- Our expected data generation is missing something
What's the difference between "rows_with_differences" and "difference_count"?
A single row comparing 5 columns could have 3 mismatches. That would be 1 row_with_differences but 3 difference_count.
How the Numbers Add Up
The metrics always satisfy this equation:
rows_matched+rows_with_differences+rows_missing=total_compared
This ensures the numbers always make sense from your perspective.
Example
If you see these results:
total_compared: 20
rows_matched: 15
rows_with_differences: 3
rows_missing: 2
difference_count: 7
This means: Out of 20 expected rows, 15 matched perfectly, 3 were found but had value differences (totaling 7 individual mismatches), and 2 couldn't be found in the extracted data at all.