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Reservoir Observations — Exact Row Deduplication + Trailing Mean Series
x402
Reservoir Observations — Exact Row Deduplication + 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 2026-10-23).
Deduplicates exact duplicate rows and computes a trailing moving-average series for supplied reservoir observation records (stored_m3, capacity_m3) — up to 200 rows, two reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Reservoir observations — Exact row deduplication + Trailing mean series: Exact row deduplication + Trailing mean series for supplied reservoir observations records (stored_m3, capacity_m3). 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
Two analytical reports: (1) a deduplicated version of the input rows with exact duplicate records removed, and (2) a trailing mean series computed over the specified rolling window for the chosen field (stored_m3 or capacity_m3), grouped or ordered by date and station_group. Both reports are derived entirely from the supplied input data with no external lookups.
Example use cases
Weekly reservoir storage trend smoothing
“I've got daily reservoir readings for 3 station groups over the past 6 months — about 180 rows. Can you remove any exact duplicate rows and then calculate a trailing 14-day moving average on the stored_m3 values so I can see the smoothed storage trend?”
Data pipeline deduplication before reporting
“Before I send our reservoir observation data into the monthly report, can you run deduplication on these 90 records and also produce a trailing mean series with a window of 5 on the capacity_m3 field to spot any anomalies in filled capacity over time?”
Multi-station reservoir monitoring cleanup
“We have records from 4 station groups — some rows got duplicated when the sensors re-synced. Can you deduplicate these 60 reservoir observation rows and give me a trailing 3-period mean for stored_m3 so I can compare smoothed levels across stations?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-19-045?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular reservoir observation data (stored_m3, capacity_m3) that needs both exact deduplication and a rolling mean smoothing in a single $0.01 call. It is ideal for batch preprocessing of up to 200 rows before ingestion into dashboards or reports. Prefer this over general-purpose analytics tools when you specifically need both deduplication and trailing mean in one lightweight, low-cost operation on hydrological time series data with no external dependencies.
Side effects
- Input array is empty or exceeds 200 rows — rejected with validation error
- Invalid date format (not YYYY-MM-DD) causes row rejection or parse error
- Window size larger than the number of rows results in incomplete or empty trailing mean series
- Null values in stored_m3 or capacity_m3 may produce gaps or NaN entries in the mean series
- Missing required fields (row_id, station_group, date) cause schema validation failure
- Payment not included or insufficient USDC causes 402 rejection before processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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