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Air Quality Observations String Normalisation
x402
Air Quality Observations String Normalisation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Normalises string fields in a batch of air quality observation records (station names, dates) and returns a descriptive string normalisation report.
Price / call$0.01
Success—
StatusUnknown
How this service works
Air quality observations - String normalisation: String normalisation for Air quality observations. 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 string normalisation report.
Output
A bounded string normalisation report covering the submitted air quality observation records (up to 200 rows). The report includes descriptive analytics on string fields such as station names and dates — covering whitespace issues, case inconsistencies, format conformance, and field-level normalisation summaries. No enrichment, forecasting, or external data is added.
Example use cases
Station name deduplication before analysis
“I've got readings from 50 monitoring stations but the station name field is inconsistent — some say 'Station A', others 'station-a' or 'STATION A'. Can you run a string normalisation pass on these air quality records so I can group them properly before doing my analysis?”
Pre-pipeline data quality check
“Before I load these 150 air quality observation rows into our database, can you normalise the string fields — especially station and date — and give me a report flagging anything that looks malformed or inconsistent?”
Automated cleaning for daily ingestion
“Every day I receive a CSV of air quality readings with row IDs, station names, dates in YYYY-MM-DD format, PM2.5 values, and humidity percentages. Can you normalise the string fields and tell me if anything looks off so I can catch data quality issues early?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-air-quality-observations-normalise?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to clean and standardise string fields (station names, date formats) in a batch of up to 200 air quality observations before downstream analysis, storage, or reporting. It is ideal for pre-pipeline data quality checks and local descriptive analytics without requiring external enrichment or forecasting. Prefer it over general-purpose data cleaning tools when your data is specifically structured air quality observations with PM2.5 and humidity fields.
Side effects
- Fewer than 1 row or more than 200 rows submitted — schema validation error
- row_id missing or empty — required field violation
- date field does not match YYYY-MM-DD pattern — pattern validation failure
- pm25 or humidity_percent values outside numeric bounds — range error
- Additional properties included in row objects — rejected due to additionalProperties:false
- Payment not received or USDC balance insufficient — 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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