{"uid":"cap_8Y7gmKp4G2BSfpOTZa3sD","slug":"join-coverage-analytics-adjacent-row-changes-equal-width-histogram-e82380cd","name":"Join Coverage Analytics: Adjacent Row Changes + Equal-Width Histogram","description":"Join coverage — Adjacent row changes + Equal-width histogram: Adjacent row changes + Equal-width histogram for supplied join coverage records (matched_rows, source_rows). 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-156?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"bins":{"type":"integer","default":5,"maximum":30,"minimum":1},"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","matched_rows","source_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"matched_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_rows":1,"matched_rows":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_rows":2,"matched_rows":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["matched_rows","source_rows"],"type":"string","default":"matched_rows"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_8ptACRwGaYxnyPjfAijD1","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs two local statistical reports on join coverage data (matched_rows, source_rows): adjacent row-to-row change analysis and an equal-width histogram, for up to 200 rows.","exampleAgentPrompt":"Analyze my join coverage data for the 'sales' group — here are 5 rows with matched_rows and source_rows values dated 2024-01-01 through 2024-01-05 — run the adjacent row changes report and a 10-bin equal-width histogram on matched_rows.","exampleUseCases":[{"title":"ETL pipeline join quality audit","prompt":"I have daily join coverage records for my ETL pipeline — 30 rows with matched_rows and source_rows from January 2024. Can you run the adjacent row changes report and a 5-bin histogram on matched_rows so I can see where coverage drops between days?"},{"title":"Data distribution check for source rows","prompt":"Here are 50 join coverage records grouped by 'warehouse' and 'retail' datasets with source_rows counts — can you compute a 10-bin equal-width histogram on source_rows to see how the values are distributed across ranges?"},{"title":"Detecting coverage spikes between records","prompt":"I need to spot sudden jumps in matched_rows across these 20 consecutive join coverage records from my nightly sync — run the adjacent row changes analysis on matched_rows so I can flag any large deltas between rows."}],"resultDescription":"Returns two independent analytical reports: (1) an adjacent row changes report showing the delta in the chosen field (matched_rows or source_rows) between each consecutive record, and (2) an equal-width histogram dividing the field values into the specified number of bins with frequency counts per bin. All computation is performed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request rejected due to maxItems constraint","Missing required fields (row_id, date, dataset_group, matched_rows, source_rows) on any row — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Bins parameter out of range (below 1 or above 30) — rejected","All values null for chosen field — histogram may be empty or degenerate","Payment of 0.01 USDC not completed — 402 payment required response"],"whenToPreferThis":"Choose this endpoint when you have structured join coverage records with matched_rows and source_rows values and need both a temporal/sequential change analysis and a frequency distribution in one call. It is ideal for data engineers auditing ETL pipeline join quality, data quality teams monitoring coverage metrics, or analysts who want a quick dual statistical snapshot without setting up local tooling. It is not a live data connector or prediction service — you must supply all rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:39.884Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-adjacent-row-changes-equal-width-histogram-e82380cd"}