{"uid":"cap_fh8x9NvdAdOws1kynOnhA","slug":"join-coverage-string-normalisation-equal-width-histogram-d63d0173","name":"Join Coverage — String Normalisation + Equal-Width Histogram","description":"Join coverage — String normalisation + Equal-width histogram: String normalisation + 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-09-031?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_F9GjzAFk4QbS9wFbwMRZj","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 analytical reports (string normalisation and equal-width histogram) on join coverage records containing matched_rows and source_rows fields, for up to 200 rows.","exampleAgentPrompt":"Can you run string normalisation and a 10-bin equal-width histogram on these join coverage records — use matched_rows as the target field? I have 4 rows across two groups: group-a on 2026-10-01 with source_rows=1 and matched_rows=10, group-b on 2026-10-02 with source_rows=2 and matched_rows=20, group-a on 2026-10-03 with source_rows=3 and matched_rows=15, and group-b on 2026-10-04 with source_rows=4 and matched_rows=30.","exampleUseCases":[{"title":"ETL pipeline join quality check","prompt":"I have 50 daily join coverage records across three dataset groups and I want to see the distribution of matched_rows — can you normalise the string labels and give me an equal-width histogram with 5 bins?"},{"title":"Source row coverage spread analysis","prompt":"Run a string normalisation and 8-bin equal-width histogram on my join coverage data using source_rows as the field — I need to understand how evenly rows are distributed across my pipeline groups."},{"title":"Data quality review before merge","prompt":"Before I merge these datasets, can you normalise the group names and show me a histogram (10 bins) of matched_rows for my join coverage records so I can spot any gaps or skew?"}],"resultDescription":"Returns two analytical reports for the submitted join coverage rows: (1) a string normalisation report cleaning and standardising dataset_group and row_id labels, and (2) an equal-width histogram report showing the frequency distribution of the chosen field (matched_rows or source_rows) bucketed into the specified number of equal-width bins. Both reports are computed locally with no external lookups.","failureModes":["Exceeds 200-row limit — request is rejected","Invalid date format (not YYYY-MM-DD) causes schema validation failure","bins value outside 1–30 range returns validation error","Null values in matched_rows or source_rows may affect histogram computation","Missing required row fields (row_id, dataset_group, date) cause schema rejection","Payment of 0.01 USDC not processed — endpoint returns 402"],"whenToPreferThis":"Choose this endpoint when you need lightweight, offline statistical reporting on join coverage data — specifically when you want both string normalisation of categorical labels AND a histogram distribution in a single call for up to 200 rows. Prefer this over heavier analytics pipelines when you need fast, self-contained computation with no external dependencies, and when your dataset fits within the 200-row limit.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:50:52.702Z","isFirstParty":false,"canonicalSlug":"join-coverage-string-normalisation-equal-width-histogram-d63d0173"}