{"uid":"cap_VlAmLFtmttHxQfVZclb9y","slug":"duplicate-observations-equal-width-histogram-explicit-missing-value-094f43fe","name":"Duplicate Observations — Equal-Width Histogram + Explicit Missing-Value Fill","description":"Duplicate observations — Equal-width histogram + Explicit missing-value fill: Equal-width histogram + Explicit missing-value fill for supplied duplicate observations records (duplicate_rows, total_rows). 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-analytics-04-175?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"bins":{"type":"integer","default":5,"maximum":30,"minimum":1},"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","duplicate_rows","total_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"duplicate_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_rows":1,"dataset_group":"group-a","duplicate_rows":10},{"date":"2026-10-02","row_id":"row-2","total_rows":2,"dataset_group":"group-b","duplicate_rows":20},{"date":"2026-10-03","row_id":"row-3","total_rows":3,"dataset_group":"group-a","duplicate_rows":15},{"date":"2026-10-04","row_id":"row-4","total_rows":4,"dataset_group":"group-b","duplicate_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["duplicate_rows","total_rows"],"type":"string","default":"duplicate_rows"},"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_jbSJixoDrBfiSrGvfOhgM","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":"Analyzes duplicate_rows and total_rows data by generating an equal-width histogram and filling missing values with zero, mean, or median — returning two analytical reports for up to 200 supplied rows.","exampleAgentPrompt":"Analyze my duplicate observation records — I have up to 50 rows with duplicate_rows and total_rows fields, some of which have null values. Fill the missing duplicate_rows values using median, then bucket everything into 10 equal-width histogram bins and give me both reports.","exampleUseCases":[{"title":"Profiling duplicates across ETL pipeline datasets","prompt":"I have 120 rows of duplicate tracking data from my ETL pipeline — each row has a dataset_group, date, duplicate_rows, and total_rows. Some duplicate_rows values are null. Fill those missing values using the mean and generate a 10-bin equal-width histogram so I can see the distribution of duplicates across the dataset."},{"title":"Data quality audit with missing-value imputation","prompt":"Run a data quality check on my duplicate observation records — I'll send you 80 rows. Use zero-fill for any missing total_rows values and show me a 5-bin histogram of the total_rows field so I can spot anomalies in the distribution."},{"title":"Monthly deduplication report with null handling","prompt":"I'm preparing a monthly deduplication summary for our data warehouse. I have 200 rows of duplicate_rows and total_rows readings grouped by dataset and date. Fill any missing duplicate_rows with the median value and produce a 15-bin equal-width histogram for the duplicate_rows field."}],"resultDescription":"Returns two analytical reports: (1) an equal-width histogram of the selected numeric field (duplicate_rows or total_rows) divided into 1–30 bins, showing bin ranges and counts; (2) a missing-value fill report where null values in the selected field are replaced using zero, mean, or median imputation. Both reports are computed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request exceeds maxItems limit","Invalid date format in any row — must match YYYY-MM-DD pattern","bins value out of range — must be between 1 and 30","No rows provided — minItems is 1","Invalid enum value for field or method parameters","Numeric values outside allowed range (-1e12 to 1e12)"],"whenToPreferThis":"Choose this endpoint when you need both a histogram distribution view and missing-value imputation for duplicate observation metrics (duplicate_rows, total_rows) in a single cheap call. Ideal for data quality pipelines, ETL monitoring dashboards, or audit workflows where you want to understand the spread of duplication rates and clean nulls before downstream processing — all without sending data to an external ML or prediction service.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:18.273Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-equal-width-histogram-explicit-missing-value-094f43fe"}