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URL Canonicalization — Equal-Width Histogram + Two-Measure Correlation
x402
URL Canonicalization — Equal-Width Histogram + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Analyzes URL canonicalization records by computing an equal-width histogram over a chosen field and calculating the correlation between observed_urls and unique_urls across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
URL canonicalization — Equal-width histogram + Two-measure correlation: Equal-width histogram + Two-measure correlation for supplied url canonicalization records (observed_urls, unique_urls). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two analytical reports: (1) an equal-width histogram dividing the selected field (observed_urls or unique_urls) into the specified number of bins with counts per bin, and (2) a correlation coefficient measuring the linear relationship between observed_urls and unique_urls across the submitted rows. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Web crawl deduplication analysis
“I've got 150 rows of crawl data with site_group, date, observed_urls, and unique_urls — can you build a 10-bin equal-width histogram on observed_urls and show me the correlation between observed and unique URL counts so I can understand how much duplication is happening?”
SEO site audit URL spread
“I'm auditing URL canonicalization across 5 site groups over the past month. Can you run a histogram with 8 bins on unique_urls and correlate it against observed_urls to see if sites with more observed URLs also have more unique ones?”
Content pipeline URL dedup metrics
“Our content pipeline tracks observed_urls and unique_urls daily — can you analyze these 80 rows with a 5-bin histogram on observed_urls and compute the two-measure correlation between observed and unique URLs to help us spot inefficiencies?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-web-20-171?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have URL canonicalization data (observed vs. unique URL counts per site group and date) and need both a distribution view (histogram) and a relationship metric (correlation) in a single call. It is ideal for small-to-medium datasets of up to 200 rows where you want offline, deterministic statistical summaries without any live web lookups or external enrichment.
Side effects
- More than 200 rows submitted — exceeds maximum row limit
- Missing required fields (row_id, date, observed_urls, unique_urls) in any row — validation error
- Invalid date format (must match YYYY-MM-DD pattern)
- bins value outside allowed range 1–30 — rejected
- All rows have null values for the selected field — histogram cannot be computed
- Only one non-null data point — correlation undefined
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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