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Water Service Coverage Data Cleaner — Deduplication & Missing-Value Fill
x402
Water Service Coverage Data Cleaner — Deduplication & Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).
Deduplicates exact duplicate rows and fills missing values in water service coverage datasets (served_households, total_households) using zero, mean, or median imputation.
Price / call$0.01
Success—
StatusUnknown
How this service works
Water service coverage — Exact row deduplication + Explicit missing-value fill: Exact row deduplication + Explicit missing-value fill for supplied water service coverage records (served_households, total_households). 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.
Output
Returns two analytical reports for the submitted dataset: one covering exact row deduplication results (identifying and removing fully duplicate rows) and one covering explicit missing-value fill (replacing null values in the specified field with the chosen imputation method — zero, mean, or median). Both reports are generated from the supplied data using local analytical engines with no external lookups.
Example use cases
Municipal water access report prep
“I'm preparing a water access report and my dataset of 120 rows has duplicate entries and some null served_households values. Can you remove the exact duplicate rows and fill the missing served_households using median imputation so the data is clean for analysis?”
Utility coverage data quality fix
“Our water utility tracking spreadsheet has rows where total_households is missing and there are duplicate records for some regions. Please deduplicate the data and fill in missing total_households values using mean imputation — I have about 80 rows total.”
NGO household coverage data cleanup
“We collected water service coverage data across 12 regions over 6 months and ended up with duplicate rows and zero-fill needed for any null served_households entries. Can you clean this up — remove exact duplicates and fill missing served_households with zero — across all 200 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-19-054?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular water service coverage data (served_households, total_households) that needs both exact duplicate row removal and null value imputation in a single call, for up to 200 rows, at very low cost ($0.01 USDC). It operates entirely on supplied data with no external API calls, making it suitable for sensitive or offline datasets. Prefer alternatives if you need predictive modeling, live data lookup, professional assessment, or datasets larger than 200 rows.
Side effects
- Rows exceeding 200 items will be rejected (maxItems constraint)
- Missing required fields (row_id, region, date, served_households, total_households) cause validation failure
- Dates not matching YYYY-MM-DD pattern are rejected
- region or row_id strings exceeding 80 characters are rejected
- Numeric values outside ±1,000,000,000,000 are rejected
- Payment of 0.01 USDC must be provided via x402 protocol or request is rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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