{"uid":"cap_Dfv0ALmaENIiGpxVyJqXW","slug":"feature-availability-analytics-category-frequencies-trailing-mean-92da09db","name":"Feature Availability Analytics — Category Frequencies + Trailing Mean Series","description":"Feature availability — Category frequencies + Trailing mean series: Category frequencies + Trailing mean series for supplied feature availability records (populated_features, expected_features). 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-10-103?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","populated_features","expected_features"],"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_features":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"populated_features":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_features":1,"populated_features":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_features":2,"populated_features":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_features":3,"populated_features":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_features":4,"populated_features":30}],"maxItems":200,"minItems":1},"field":{"enum":["populated_features","expected_features"],"type":"string","default":"populated_features"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_tGIZIbPgHMYX1LnKzdm6F","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 feature availability records to produce two reports: category frequency distributions and trailing mean time series, for up to 200 rows of populated/expected feature data.","exampleAgentPrompt":"Can you run category frequency and trailing mean analysis on my feature availability data? I have 4 rows with dataset groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, populated_features values like 10, 20, 15, 30 and expected_features 1, 2, 3, 4 — use 'populated_features' as the field with a window of 3.","exampleUseCases":[{"title":"Feature coverage audit by dataset group","prompt":"I have 150 rows of feature availability records across 5 dataset groups with daily dates and populated vs expected feature counts — can you run a category frequency breakdown and a trailing mean series with a window of 7 on the populated_features field so I can see which groups are consistently underperforming?"},{"title":"Rolling average for data pipeline health","prompt":"Run a trailing mean series with a window of 5 on my expected_features column across these 80 daily pipeline records — I want to see how the smoothed trend compares to my raw values and also get the category frequency breakdown by dataset_group."},{"title":"QA report for ML feature store","prompt":"I need two quick reports on my feature store QA data: category frequencies by dataset group and a 14-day trailing mean for populated_features. I have 200 rows with row IDs, dates, and both populated and expected feature counts per record."}],"resultDescription":"Returns two analytical reports derived from the supplied rows: (1) a category frequency distribution showing how often each dataset_group appears and/or how feature values distribute across categories, and (2) a trailing mean time series computed over the specified window for the selected field (populated_features or expected_features). No external lookups or predictions are made — all computation is local to the supplied data.","failureModes":["Fewer than 1 row or more than 200 rows supplied — request rejected","Window size larger than the number of rows — trailing mean may be undefined or reduced","Missing required fields (row_id, date, populated_features, expected_features) — validation error","Malformed date strings not matching YYYY-MM-DD pattern — parse error","Null values in numeric fields may affect trailing mean computation","Invalid field enum value (not 'populated_features' or 'expected_features') — rejected"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of feature availability records and need both a category frequency distribution and a trailing mean time series in a single low-cost call ($0.01 USDC for both reports). It is ideal for lightweight, offline analytical tasks on pre-collected data where no live data fetching, predictions, or external enrichment is required. Prefer alternatives if you need more than 200 rows, real-time data ingestion, or a different type of statistical analysis (e.g. outlier detection, elasticity, period-over-period comparison).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:38.150Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-category-frequencies-trailing-mean-92da09db"}