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Museum Footfall Base-100 Index Series
x402
Museum Footfall Base-100 Index Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Converts raw museum visitor and dwell-time records into a base-100 indexed time series for descriptive analytics across exhibits.
Price / call$0.01
Success—
StatusUnknown
How this service works
Museum footfall - Base-100 series: Base-100 series for Museum footfall. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded base-100 series report.
Output
A bounded base-100 index report containing up to 200 records, each showing the indexed value for the selected field (visitors or dwell_minutes) relative to the chosen baseline row, broken down by exhibit and date. No forecasting or external enrichment is included — purely descriptive local analytics.
Example use cases
Exhibit performance benchmarking
“I have daily visitor counts for three exhibits over the past month — can you index the visitor numbers to base-100 starting from the first day so I can compare how each exhibit's attendance grew or shrank relative to that opening day?”
Dwell time trend analysis
“I want to see how average dwell time at our temporary exhibition has changed week by week — can you take my 20 rows of daily dwell_minutes data and produce a base-100 series using the first week's row as the baseline?”
Post-reopening footfall recovery report
“Our museum just reopened after renovation and I have visitor counts per exhibit for each day since reopening — index them all to base-100 from the reopening day so I can show trustees how quickly attendance recovered.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-museum-footfall-index?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw tabular museum visitor or dwell-time records and need a quick, local base-100 normalization for descriptive comparison across exhibits or time periods — without needing forecasting, external enrichment, or large-scale data processing. Ideal for small to medium datasets (up to 200 rows) where the goal is relative trend visualization or stakeholder reporting at very low cost ($0.01 per call).
Side effects
- Fewer than 1 row supplied returns a validation error
- More than 200 rows supplied exceeds the maxItems limit and is rejected
- base_index pointing to a non-existent row index causes an out-of-bounds error
- Null values in the selected field on the base row may produce undefined or zero-division behavior
- Malformed date strings not matching YYYY-MM-DD pattern fail schema validation
- Missing required fields (row_id, exhibit, date, visitors, dwell_minutes) cause request rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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