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Water Service Coverage — Duplicate Key Report + Trailing Mean Series
x402
Water Service Coverage — Duplicate Key Report + Trailing Mean Series 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).
Analyzes up to 200 rows of water service coverage data to produce a duplicate key report and a trailing mean series for served_households or total_households.
Price / call$0.01
Success—
StatusUnknown
How this service works
Water service coverage — Duplicate key report + Trailing mean series: Duplicate key report + Trailing mean series 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 independent analytical reports: (1) a duplicate key report identifying any row_id values that appear more than once in the submitted dataset, and (2) a trailing mean series computed over the selected field (served_households or total_households) using the specified window size. Both reports are derived entirely from the supplied data with no external lookups.
Example use cases
Audit water utility data for duplicate keys
“I have a CSV of water service coverage records with row IDs, regions, dates, served_households, and total_households — can you run a duplicate key report to find any repeated row IDs and also give me a trailing mean of served_households with a window of 4?”
Compute rolling average for household coverage
“Run a trailing mean analysis on my water service total_households data using a window of 5, and flag any duplicate row IDs in the dataset — I'll paste in about 80 rows with row_id, region, date, served_households, and total_households.”
Data quality check before water coverage reporting
“Before I submit this quarterly water coverage report, can you check my 120 rows for duplicate row keys and compute a rolling mean of served_households with a window of 2, so I can spot anomalies?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-19-061?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular water service coverage data and need both data quality validation (duplicate key detection) and time-series smoothing (trailing mean) in a single low-cost call. Ideal for pre-reporting data audits or pipeline QA steps where you want two analytical outputs without separate API calls. Not suitable if you need live data fetching, predictions, or professional utility assessments.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Invalid date format (not YYYY-MM-DD) — validation error
- Missing required fields (row_id, region, date) — schema validation failure
- Window size outside 2–200 range — parameter error
- Empty rows array — minimum items constraint violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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