{"uid":"cap_VhD_uLy2piRCC2g1a4Sgl","slug":"market-survey-observations-base-100-series-explicit-missing-value-fill-2c9d2636","name":"Market Survey Observations — Base-100 Series + Explicit Missing-Value Fill","description":"Market survey observations — Base-100 series + Explicit missing-value fill: Base-100 series + Explicit missing-value fill for supplied market survey observations records (respondent_count, sample_weight). 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-company-06-169?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","respondent_count","sample_weight"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"sample_weight":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"respondent_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","sample_weight":1,"respondent_count":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","sample_weight":2,"respondent_count":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","sample_weight":3,"respondent_count":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","sample_weight":4,"respondent_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["respondent_count","sample_weight"],"type":"string","default":"respondent_count"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"},"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_Hxw4WgXEZxQDO34X9qReY","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 a base-100 indexed time series and fills missing values (zero, mean, or median) for market survey observation records containing respondent counts and sample weights.","exampleAgentPrompt":"I have market survey data with respondent counts and sample weights for groups A and B across October 2026 — can you normalize it to a base-100 series starting at row index 0 and fill any missing respondent_count values using median imputation?","exampleUseCases":[{"title":"Normalize survey trends across company groups","prompt":"Take my market survey observations for group-a and group-b from Q4 2026 and create a base-100 indexed series for respondent_count starting from the first row, filling any missing values with the median."},{"title":"Impute missing sample weights in survey data","prompt":"I have 150 rows of market survey records with some null sample_weight values — can you run a base-100 normalization on sample_weight with zero-fill for the missing entries, using row index 0 as the base?"},{"title":"Benchmark survey respondent counts to baseline","prompt":"Here are my market survey observation records across multiple company groups. Please index the respondent_count field to base-100 starting at row 2 and fill any gaps using mean imputation so I can compare trends fairly."}],"resultDescription":"Returns two analytical reports: (1) a base-100 indexed time series for the chosen field (respondent_count or sample_weight) anchored at the specified base index row, and (2) the same dataset with explicit missing-value fill applied using the chosen method (zero, mean, or median). Covers up to 200 input rows, processed locally without external lookups.","failureModes":["Input array is empty (minItems:1 violated) — request rejected","More than 200 rows submitted (maxItems:200 violated) — request rejected","base_index out of bounds (exceeds number of rows minus 1) — may produce error or undefined base","Invalid date format (must match YYYY-MM-DD) — validation error","Field or method enum value not recognized — defaults applied or error returned","All values for chosen field are null — base-100 computation may be undefined"],"whenToPreferThis":"Use this endpoint when you have tabular market survey data (up to 200 rows) with respondent_count or sample_weight fields and need both a base-100 normalized index series and explicit missing-value imputation in a single call. Prefer this over generic analytics tools when you want deterministic, reproducible local computation without live external lookups, and when your data is already structured with row_id, company_group, and date identifiers.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:35.742Z","isFirstParty":false,"canonicalSlug":"market-survey-observations-base-100-series-explicit-missing-value-fill-2c9d2636"}