{"uid":"cap_fAZ-V-GyuTVoF0wvug7QE","slug":"social-post-observations-adjacent-row-changes-explicit-missing-value-64b5e3dc","name":"Social Post Observations — Adjacent Row Changes + Explicit Missing-Value Fill","description":"Social post observations — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied social post observations records (impressions, engagement_count). 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-news-13-162?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","channel_group","date","impressions","engagement_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"impressions":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"channel_group":{"type":"string","default":"","maxLength":80},"engagement_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","impressions":10,"channel_group":"group-a","engagement_count":1},{"date":"2026-10-02","row_id":"row-2","impressions":20,"channel_group":"group-b","engagement_count":2},{"date":"2026-10-03","row_id":"row-3","impressions":15,"channel_group":"group-a","engagement_count":3},{"date":"2026-10-04","row_id":"row-4","impressions":30,"channel_group":"group-b","engagement_count":4}],"maxItems":200,"minItems":1},"field":{"enum":["impressions","engagement_count"],"type":"string","default":"impressions"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_e5TKM-fN-BMHA1suZdnWV","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 adjacent-row changes and fills missing values (impressions or engagement_count) for up to 200 social post observation records using local analytical engines.","exampleAgentPrompt":"I have 150 rows of social post data with dates, channel groups, impressions, and engagement counts — some impressions values are missing. Can you compute the adjacent row changes for impressions and fill the missing impressions values using median, across all rows?","exampleUseCases":[{"title":"Clean sparse social post impressions dataset","prompt":"I've got a dataset of 80 social post observations across different channel groups and dates, but about 15 of the impressions values are null. Can you fill in those missing impressions values using the median method and also show me how impressions changed row by row?"},{"title":"Row-over-row engagement change analysis","prompt":"Here are 120 rows of social post records with engagement counts and impressions by date and channel group. I need to see the adjacent row changes for engagement_count and fill any missing engagement_count values with zero — can you run both reports?"},{"title":"Multi-channel content performance cleanup","prompt":"I'm auditing our social content data — I have about 200 rows with channel_group, date, impressions, and engagement_count. Some engagement_count entries are missing. Please fill them with the mean and compute how each row's engagement_count changed relative to the previous row."}],"resultDescription":"Returns two analytical reports: (1) an adjacent row changes report showing the delta between consecutive rows for the specified field (impressions or engagement_count), and (2) an explicit missing-value fill report where nulls in the target field are replaced using the chosen method (zero, mean, or median). Both reports operate on the supplied dataset of up to 200 social post observation rows.","failureModes":["More than 200 rows submitted — request rejected due to maxItems constraint","Invalid date format (not YYYY-MM-DD) — validation error","Missing required fields (row_id, channel_group, date) — schema validation failure","Field value out of allowed numeric range — validation error","Invalid enum value for 'field' or 'method' — rejected"],"whenToPreferThis":"Choose this endpoint when you have social post observation data (with impressions and/or engagement_count fields) that needs row-over-row delta analysis and missing-value imputation in a single, low-cost call. It is ideal for data cleaning and trend-detection pipelines where you need both change detection and gap-filling without external lookups or predictions, and where your dataset fits within 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:52:54.591Z","isFirstParty":false,"canonicalSlug":"social-post-observations-adjacent-row-changes-explicit-missing-value-64b5e3dc"}