{"uid":"cap_Lr8bWxygGChFCtiVxKF1M","slug":"company-headcount-observations-string-normalisation-missing-value-fill-e0879237","name":"Company Headcount Observations — String Normalisation & Missing-Value Fill","description":"Company headcount observations — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied company headcount observations records (headcount, open_roles). 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-12-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","headcount","open_roles"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"headcount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"open_roles":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","headcount":10,"open_roles":1,"company_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","headcount":20,"open_roles":2,"company_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","headcount":15,"open_roles":3,"company_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","headcount":30,"open_roles":4,"company_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["headcount","open_roles"],"type":"string","default":"headcount"},"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_w73PTFShwZjcDVn52S97u","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":"Normalises string fields and fills missing values (headcount or open_roles) in company headcount observation records using zero, mean, or median imputation across up to 200 rows.","exampleAgentPrompt":"Can you clean up my company headcount dataset — I have up to 50 rows with company_group, date, headcount, and open_roles fields, some of which have null headcount values — fill the missing headcount entries using median imputation and normalise the string fields?","exampleUseCases":[{"title":"Imputing missing headcount before reporting","prompt":"I have a set of 80 company headcount observations across several groups with some null headcount values — can you fill those gaps using median imputation and normalise the string fields so I can feed the cleaned data into my monthly workforce report?"},{"title":"Cleaning open_roles data with zero fill","prompt":"My HR dataset has about 120 rows tracking open_roles by company group and date, but several entries are missing — please fill those missing open_roles values with zero and normalise any inconsistent string formatting across the records."},{"title":"Standardising headcount records for a BI pipeline","prompt":"Before I load our headcount observation records into the data warehouse, I need the strings normalised and any null headcount values replaced with the mean — can you process these 200 rows and give me back the cleaned dataset?"}],"resultDescription":"Returns two analytical reports for the submitted rows: one covering string normalisation applied to the company_group and date fields, and one covering explicit missing-value imputation for the selected field (headcount or open_roles) using the chosen method (zero, mean, or median). Output reflects cleaned, standardised records ready for downstream analysis.","failureModes":["Rows array exceeds 200 items — request rejected","Missing required fields (row_id, company_group, date, headcount, open_roles) on any row — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Unknown imputation method value — enum mismatch error","All values already present — imputation report will show no changes made","Payment not included or insufficient — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have tabular company headcount or open_roles observation data that needs string field normalisation and missing-value imputation in a single lightweight call. It is ideal for pre-processing HR or workforce datasets of up to 200 rows before loading into analytics pipelines or BI tools. Prefer it over general-purpose data tools when you specifically need the combination of string normalisation and explicit null fill (zero, mean, or median) on headcount or open_roles columns without requiring live data lookup or external enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:03.304Z","isFirstParty":false,"canonicalSlug":"company-headcount-observations-string-normalisation-missing-value-fill-e0879237"}