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Temperature Observations — String Normalisation + Two-Measure Correlation
x402
Temperature Observations — String Normalisation + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Normalises station group strings and computes correlation between temperature_c and observation_count across up to 200 temperature observation rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Temperature observations — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied temperature observations records (temperature_c, observation_count). 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 string normalisation report on the station_group field, cleaning and standardising group name values across all input rows; and (2) a correlation report quantifying the statistical relationship between temperature_c and observation_count across the supplied rows (up to 200). No external data is fetched; all analysis is performed locally on the supplied rows.
Example use cases
Weather station data quality audit
“I've got 120 rows of temperature readings from various station groups with messy naming — can you normalise the station_group strings and also tell me whether temperature_c correlates with observation_count across those rows?”
Climate dataset correlation check
“Here are 80 temperature observation records from our monitoring network with dates, temperatures in Celsius, and observation counts per day — please run string normalisation on the station group labels and give me a correlation report between the two numeric measures.”
Research data preparation for temperature logs
“I'm preparing temperature observation data for a report — I have 40 rows with row IDs, station groups, dates, temperature_c values, and observation counts. Can you normalise the group name strings and compute a two-measure correlation between temperature and observation count?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-01-033?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation of categorical station/group labels AND a two-measure numeric correlation on temperature and observation count fields within a single call on up to 200 rows of temperature observation data. It is a local analytical service with no live lookups or external predictions, making it suitable for offline data preparation and quality workflows where a cheap, deterministic computation ($0.01 USDC for two reports) is preferred over heavyweight analytics platforms.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, date, temperature_c, observation_count) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers schema rejection
- All-null temperature_c or observation_count values may prevent meaningful correlation calculation
- Malformed JSON body returns an error response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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