{"uid":"cap_uSA-EgQJz--1y7v90QxAw","slug":"time-series-completeness-numeric-distribution-base-100-series-31c33b9d","name":"Time Series Completeness — Numeric Distribution + Base-100 Series","description":"Time series completeness — Numeric distribution + Base-100 series: Numeric distribution + Base-100 series 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-16-078?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_b3QeE1C9aYf9mF5bGMaeH","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":"Analyzes time series completeness records (observed vs expected data points) by generating both a numeric distribution report and a base-100 rebase series for up to 200 rows.","exampleAgentPrompt":"I have daily time series completeness data for two groups over October 2026 — can you run a numeric distribution report AND a base-100 series rebased from index 0 on the observed_points field? Here are the rows: group-a on 2026-10-01 had 10 observed out of 1 expected, group-b on 2026-10-02 had 20 observed out of 2 expected, group-a on 2026-10-03 had 15 observed out of 3 expected, group-b on 2026-10-04 had 30 observed out of 4 expected.","exampleUseCases":[{"title":"Audit sensor data pipeline completeness","prompt":"I have 30 days of IoT sensor readings where I know how many readings were expected each day and how many actually arrived — can you generate a numeric distribution and a base-100 series starting from day 0 for the observed_points so I can see where gaps are worst?"},{"title":"Monitor ETL job data delivery gaps","prompt":"My ETL pipeline tracks expected vs observed records delivered daily across 3 dataset groups over the last 90 days. Can you run both a numeric distribution and a base-100 rebase report on the expected_points field starting at index 0 so I can see the spread and trend?"},{"title":"Compare completeness across survey dataset groups","prompt":"I've got completeness records for 5 survey dataset groups — each row has a date, group name, how many responses we expected, and how many we got. Run a numeric distribution and base-100 series on observed_points rebased from the first row so I can compare group performance."}],"resultDescription":"Returns two independent analytical reports sharing the same input data: (1) a numeric distribution report showing the statistical spread (bins, frequencies, percentiles) of the selected field across all rows, and (2) a base-100 rebase series that re-indexes values relative to the specified base row, enabling trend comparison. Both reports cover up to 200 supplied rows with no external data lookup.","failureModes":["Input array is empty or exceeds 200 rows — validation error returned","base_index value exceeds the number of supplied rows — out-of-range error","required fields (row_id, date, observed_points, expected_points) missing from any row — schema validation failure","date strings not in YYYY-MM-DD format — pattern validation error","observed_points or expected_points outside allowed numeric range — validation error","Payment of 0.01 USDC not settled via x402 — request rejected"],"whenToPreferThis":"Choose this endpoint when you need two complementary statistical views — a numeric distribution AND a base-100 indexed series — of time series completeness data in a single low-cost call. It is ideal for data quality monitoring workflows where you want both a spread analysis and a normalized trend comparison from supplied data without any external lookups or live data fetching. Prefer it over single-report endpoints when you need both report types simultaneously for up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:48.506Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-numeric-distribution-base-100-series-31c33b9d"}