{"uid":"cap_m5G-8vBGxCRlryYj7Adft","slug":"recruitment-funnel-explicit-missing-value-fill-9f1a730a","name":"Recruitment Funnel – Explicit Missing-Value Fill","description":"Recruitment funnel - Explicit missing-value fill: Explicit missing-value fill for Recruitment funnel. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded explicit missing-value fill deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-analytics-recruitment-funnel-fill-missing?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","source","date","applications","interviews"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source":{"type":"string","default":"","maxLength":80},"interviews":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"applications":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source":"group-a","interviews":1,"applications":10},{"date":"2026-10-02","row_id":"row-2","source":"group-b","interviews":2,"applications":20},{"date":"2026-10-03","row_id":"row-3","source":"group-a","interviews":3,"applications":15},{"date":"2026-10-04","row_id":"row-4","source":"group-b","interviews":4,"applications":30}],"maxItems":200,"minItems":1},"field":{"enum":["applications","interviews"],"type":"string","default":"applications"},"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_oTjXo1EoVqdT9_6TorGzH","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":"Fills missing numeric values (applications or interviews) in recruitment funnel records using zero, mean, or median imputation methods","exampleAgentPrompt":"I have a recruitment funnel dataset with up to 200 rows — some 'applications' values are null. Can you fill those missing values using the median method? Here's a sample: row-1, 2026-10-01, group-a, applications=null, interviews=3; row-2, 2026-10-02, group-b, applications=20, interviews=null.","exampleUseCases":[{"title":"Imputing missing interview counts","prompt":"My hiring funnel data has several rows where the interviews column is null. Can you fill those missing interview values using the mean of the available data? I have about 50 rows across multiple sources and dates."},{"title":"Cleaning applications data before reporting","prompt":"Before I run my weekly recruitment report, I need to fill in the null values in my applications column using zero — I have 120 rows of funnel data with dates, sources, and some missing application counts."},{"title":"Data quality prep for recruitment dashboard","prompt":"I'm loading recruitment funnel records into our dashboard but some rows are missing application numbers. Can you impute those nulls using the median so the pipeline metrics don't break? I've got around 80 rows to process."}],"resultDescription":"Returns the recruitment funnel records with missing values in the specified field (applications or interviews) filled using the chosen method (zero, mean, or median), providing a complete dataset ready for downstream analytics or reporting.","failureModes":["Validation error if required fields (row_id, source, date, applications, interviews) are missing from any row","Error if more than 200 rows are submitted (maxItems limit)","Error if date format does not match YYYY-MM-DD pattern","Error if field enum value is not 'applications' or 'interviews'","Error if method enum value is not 'zero', 'mean', or 'median'","Empty or malformed payload returns schema validation failure"],"whenToPreferThis":"Choose this endpoint when you have recruitment funnel tabular data (up to 200 rows) with null or missing numeric values in the applications or interviews columns and need a simple, local statistical imputation (zero, mean, or median) without external enrichment. It is ideal for lightweight data-cleaning steps in HR analytics pipelines before aggregation or visualization.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T00:54:02.648Z","isFirstParty":false,"canonicalSlug":"recruitment-funnel-explicit-missing-value-fill-9f1a730a"}