{"uid":"cap_2OSkBE1bsl38XSvWutP6-","slug":"field-survey-coverage-data-quality-pipeline-d6d80b86","name":"Field Survey Coverage Data Quality Pipeline","description":"Field survey coverage — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied field survey coverage records (surveyed_m2, target_m2). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-weather-22-208?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","surveyed_m2","target_m2"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"target_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"surveyed_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","target_m2":1,"surveyed_m2":10,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","target_m2":2,"surveyed_m2":20,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","target_m2":3,"surveyed_m2":15,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","target_m2":4,"surveyed_m2":30,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["surveyed_m2","target_m2"],"type":"string","default":"surveyed_m2"},"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_1DgSb998eK9pOtuNNpU1l","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":"Audits field survey coverage records for quality issues, normalises strings, and fills missing values in surveyed_m2 or target_m2 fields across up to 200 rows, returning 3 independent analytical reports.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and median missing-value fill on my field survey coverage rows — the data has row IDs, station groups, dates, and surveyed_m2 and target_m2 measurements — I have about 50 rows and want to fill gaps in the surveyed_m2 field using median imputation?","exampleUseCases":[{"title":"Pre-analysis survey data cleaning","prompt":"I have 120 field survey records with station_group labels, dates, and surveyed_m2 and target_m2 values — some surveyed_m2 entries are missing. Can you audit the record quality, normalise the station group strings, and fill those missing surveyed_m2 values using the mean method so my data is ready for analysis?"},{"title":"Ecological coverage completeness check","prompt":"Before I submit our seasonal survey dataset can you check the record quality and flag any issues in our surveyed_m2 and target_m2 columns, normalise any inconsistent station group names, and fill any nulls in target_m2 using zero fill? We have about 80 rows."},{"title":"Survey pipeline data validation","prompt":"Run a full data quality pipeline on these 200 field survey coverage rows — I need the record quality audit, string normalisation on station_group, and median imputation for any missing surveyed_m2 values, and give me all three reports."}],"resultDescription":"Three independent analytical reports covering: (1) a record quality audit flagging completeness, format issues, and anomalies in the survey records; (2) a string normalisation report showing standardised station_group and other string fields; and (3) a missing-value fill report showing which surveyed_m2 or target_m2 nulls were imputed and with what values (zero, mean, or median). All computed locally with no external lookups.","failureModes":["More than 200 rows submitted — request rejected with maxItems validation error","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Missing required fields (row_id, station_group, date) trigger required-field errors","Numeric values outside ±1,000,000,000,000 range cause schema rejection","Invalid method enum value (not zero/mean/median) causes validation error","Invalid field enum value (not surveyed_m2/target_m2) causes validation error","Empty rows array (minItems:1 violation) returns validation error"],"whenToPreferThis":"Choose this endpoint when you have field survey coverage data (with surveyed_m2 and target_m2 measurements) that needs a combined data quality audit, string normalisation, and missing-value imputation in a single call returning three structured reports. It is ideal for pre-processing survey datasets before statistical analysis, with no need for external data, predictions, or live lookups. At $0.01 USDC for three reports on up to 200 rows it is cost-effective for batch data cleaning pipelines.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:49:59.729Z","isFirstParty":false,"canonicalSlug":"field-survey-coverage-data-quality-pipeline-d6d80b86"}