{"uid":"cap_FL3xoUl6uanNbNB6WdL4Y","slug":"time-series-completeness-numeric-row-ordering-equal-width-histogram-4cc4da18","name":"Time Series Completeness — Numeric Row Ordering + Equal-Width Histogram","description":"Time series completeness — Numeric row ordering + Equal-width histogram: Numeric row ordering + Equal-width histogram for supplied time series completeness records (observed_points, expected_points). 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-16-118?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","observed_points","expected_points"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"expected_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observed_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_points":1,"observed_points":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_points":2,"observed_points":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_points":3,"observed_points":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_points":4,"observed_points":30}],"maxItems":200,"minItems":1},"field":{"enum":["observed_points","expected_points"],"type":"string","default":"observed_points"}}},"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_QtWkWlSfL2ZZI8rmgsY5g","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":"Generates two local analytical reports (numeric row ordering and equal-width histogram) for time series completeness data (observed vs. expected points) across up to 200 rows.","exampleAgentPrompt":"Can you run a numeric row ordering and equal-width histogram analysis on my time series completeness records? I have 50 rows with observed_points and expected_points per date across two dataset groups — use 10 bins and analyze the observed_points field.","exampleUseCases":[{"title":"Audit sensor data completeness gaps","prompt":"I have 120 rows of daily sensor readings with observed and expected data points per dataset group. Can you run a numeric row ordering and equal-width histogram on the observed_points field with 8 bins so I can see where completeness gaps cluster?"},{"title":"Profile ETL pipeline expected vs actual throughput","prompt":"My ETL pipeline logs have 80 rows showing expected_points and observed_points per date. Run both the numeric ordering and histogram reports on expected_points with 5 bins so I can understand the distribution and sequence of what was expected."},{"title":"Detect distribution skew in multi-group time series","prompt":"I've got completeness records across three dataset groups, about 150 rows total, each with a date, observed_points, and expected_points. Can you do a numeric row ordering plus a 15-bin equal-width histogram on the observed_points to see if any groups are heavily skewed?"}],"resultDescription":"Returns two analytical reports: (1) a numeric row ordering of the supplied rows ranked by the chosen field (observed_points or expected_points), and (2) an equal-width histogram dividing the field's value range into the specified number of bins with counts per bin. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["More than 200 rows supplied — request rejected","Missing required row fields (row_id, date, observed_points, expected_points) — validation error","Invalid date format (must match YYYY-MM-DD) — schema validation failure","bins value outside 1–30 range — rejected","All values null for the selected field — histogram cannot be computed","Network or payment failure — HTTP 402 or 5xx error"],"whenToPreferThis":"Choose this endpoint when you need quick, self-contained analytical profiling of time series completeness data — specifically numeric ordering and histogram distribution — without requiring external data sources, predictions, or professional assessments. It is ideal for datasets up to 200 rows where you want both a ranked sequence view and a binned frequency distribution in a single low-cost call. Prefer it over general-purpose analytics services when your data is already structured as observed/expected point pairs per date and group.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:39:17.962Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-numeric-row-ordering-equal-width-histogram-4cc4da18"}