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Trixie Lasagne Statistical Analysis
x402
Trixie Lasagne Statistical Analysis is a paid API for AI agents from trixielasagne-api.purplewater-b02e2643.eastus.azurecontainerapps.io, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-13).
Performs deterministic statistical analysis (describe, percentiles, correlation, outlier detection, time-series) over caller-supplied tabular data
Price / call$0.01
Success—
StatusUnknown
How this service works
Deterministic statistical analysis (describe, percentiles, correlation, outliers, time-series) over caller-supplied data
Output
Returns structured statistical results depending on the method requested: descriptive statistics (mean, median, std dev, min, max), percentile breakdowns, pairwise correlation coefficients, flagged outlier rows, or time-series decomposition metrics — all computed deterministically from the supplied data.
Example use cases
Outlier detection in sales data
“I have a table of daily sales figures for the past year — can you run an outlier analysis on it and flag any days where sales were statistically unusual?”
Descriptive stats on survey results
“Here's a dataset of 500 survey responses with numeric ratings — give me the mean, median, standard deviation, and percentile breakdown for each question column.”
Correlation analysis for financial variables
“I've got a dataset with monthly revenue, ad spend, and headcount — can you check which of these variables are correlated with each other and how strongly?”
Technical details
Endpoint
POSThttps://trixielasagne-api.purplewater-b02e2643.eastus.azurecontainerapps.io/stats/analyseWhen to prefer
Choose this endpoint when you need deterministic, reproducible statistical analysis on data you already hold — especially for describe, percentile, correlation, outlier, or time-series methods — and want a lightweight per-call cost model at $0.01 USDC rather than spinning up a full analytics environment. Prefer it over general code-execution endpoints when you want structured JSON statistical output without managing a runtime.
Side effects
- Missing or malformed 'input' field returns a validation error
- Non-numeric columns passed to numeric methods cause computation errors
- Empty dataset body results in an empty or error response
- Unsupported method name returns an unknown method error
- Payment not included or insufficient causes a 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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