{"uid":"cap_0mUnMvh_w4W-xFha6_6bk","slug":"data-ingestion-batches-equal-width-histogram-iqr-outlier-flags-fe8a37d3","name":"Data Ingestion Batches — Equal-Width Histogram + IQR Outlier Flags","description":"Data ingestion batches — Equal-width histogram + IQR outlier flags: Equal-width histogram + IQR outlier flags for supplied data ingestion batches records (received_rows, accepted_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-01-170?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","received_rows","accepted_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"accepted_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"received_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","accepted_rows":1,"dataset_group":"group-a","received_rows":10},{"date":"2026-10-02","row_id":"row-2","accepted_rows":2,"dataset_group":"group-b","received_rows":20},{"date":"2026-10-03","row_id":"row-3","accepted_rows":3,"dataset_group":"group-a","received_rows":15},{"date":"2026-10-04","row_id":"row-4","accepted_rows":4,"dataset_group":"group-b","received_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["received_rows","accepted_rows"],"type":"string","default":"received_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_l0tcOsNgYN4lF6B4vEbdc","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":"Computes equal-width histograms and IQR-based outlier flags for received_rows and accepted_rows fields across up to 200 data ingestion batch records.","exampleAgentPrompt":"Can you analyze the distribution and flag outliers in our ingestion batch data? Here are 5 records with received_rows and accepted_rows — use 10 bins and analyze the received_rows field: row-1 on 2024-01-01, group-a, 500 received/480 accepted; row-2 on 2024-01-02, group-b, 12000 received/11800 accepted; row-3 on 2024-01-03, group-a, 490 received/470 accepted; row-4 on 2024-01-04, group-b, 510 received/505 accepted; row-5 on 2024-01-05, group-a, 480 received/460 accepted.","exampleUseCases":[{"title":"Detecting spike days in pipeline ingestion","prompt":"I have 30 days of ingestion batch records with received_rows and accepted_rows — can you run a histogram with 8 bins and IQR outlier detection on accepted_rows to find which days had abnormally low acceptance counts?"},{"title":"QA report on data acceptance rates","prompt":"We just finished a month-long ingestion run across two dataset groups. Can you analyze these 60 batch records for me — use 5 bins and flag any IQR outliers in the received_rows field so I know which batches were statistically unusual?"},{"title":"Comparing ingestion volume distribution across groups","prompt":"Here are 150 ingestion records from our ETL pipeline for group-alpha and group-beta. Can you build a histogram with 15 bins on received_rows and tell me which records fall outside the IQR bounds?"}],"resultDescription":"Returns two independent statistical reports (one per field: received_rows and accepted_rows) each containing: an equal-width histogram showing bin ranges and counts, and IQR-based outlier flags identifying which rows fall below Q1−1.5×IQR or above Q3+1.5×IQR.","failureModes":["Exceeds 200 row limit — request rejected","Invalid date format (not YYYY-MM-DD) — schema validation error","bins value outside 1–30 range — rejected","Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) — validation failure","All values null for a field — histogram and IQR cannot be computed","Payment not included or insufficient — 402 response"],"whenToPreferThis":"Use this endpoint when you have up to 200 data ingestion batch records and need fast, local statistical analysis — specifically equal-width histograms and IQR outlier flagging — on received_rows or accepted_rows. Ideal for data engineering QA workflows, pipeline monitoring, or anomaly detection on ingestion metrics without sending data to an external ML service. Prefer this over general-purpose analytics APIs when you need deterministic, reproducible statistical summaries with outlier flags on structured tabular ingestion data at low cost ($0.01 per call covering both fields).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T00:52:36.568Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-equal-width-histogram-iqr-outlier-flags-fe8a37d3"}