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Savings Ledger — String Normalisation + Trailing Mean Series
x402
Savings Ledger — String Normalisation + 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 2026-10-30).
Runs two local analytical reports on savings ledger rows: string normalisation of categorical fields and a trailing moving-average series for deposit or withdrawal amounts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Savings ledger — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied savings ledger records (deposit_amount, withdrawal_amount). 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 reports for up to 200 supplied rows: (1) a string normalisation report standardising categorical text fields such as instrument_group, and (2) a trailing moving-average series for the selected numeric field (deposit_amount or withdrawal_amount) computed over the specified rolling window. No external data is fetched; all analysis is performed locally on the supplied data.
Example use cases
Smooth monthly deposit trends
“I have 120 rows of savings ledger data with dates and deposit amounts — can you compute a trailing mean series with a window of 6 on deposit_amount so I can see smoothed monthly trends?”
Clean instrument group labels
“My savings ledger has messy instrument_group strings across 80 rows — please run string normalisation on those labels so they're consistent, along with a trailing mean on withdrawal_amount using a window of 3.”
Audit withdrawal volatility
“Can you analyse my 200-row savings ledger by running a trailing mean series on withdrawal_amount with a window of 10 and normalise the instrument_group strings at the same time?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-23-028?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two complementary analytical reports on savings ledger data — string normalisation of categorical columns and a rolling mean series for a numeric field — in a single low-cost call. It is best suited for offline, batch-style analysis of up to 200 rows with no need for live market data, predictions, or external lookups.
Side effects
- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — exceeds maximum batch size
- Invalid date format (must match YYYY-MM-DD pattern)
- Missing required fields: row_id, instrument_group, date, deposit_amount, or withdrawal_amount
- Window size less than 2 or greater than 200
- Invalid field selector — must be 'deposit_amount' or 'withdrawal_amount'
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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