Calculate Quantiles

statistics.quantile

ProductionBounded custom (Class B)Deterministicstrictfastv1.0.0

No network

Overview

You send a numeric vector and one to 101 probabilities in [0, 1]. LINEAR_R7, the default, is Hyndman–Fan type 7: h = p × (n − 1), then linear interpolation between adjacent order statistics. LOWER, HIGHER, NEAREST (half-to-even index) and MIDPOINT are the discrete alternatives. Results are ordered by probability. This is not a confidence interval, a streaming quantile, or a weighted sample.

Nine common quantile definitions disagree at the same p. Naming the method, and using type 7 as the default, makes R, NumPy and this skill comparable.

Reliability

LINEAR_R7 matches Hyndman–Fan type 7 and NumPy linear. Permuting values does not change the result. SERIES_INVALID — trigger: every observation was null under OMIT, or a null arrived under REJECT; retryable: no; next: send at least one finite number. ITEM_LIMIT_EXCEEDED — trigger: more than 100000 values or more than 101 probabilities; retryable: no; next: split the request.

Context footprint

One vector and a short probability list in. A successful call costs 1 execution credit.

When to use it

When you need one or more empirical quantiles and must name the interpolation.

When you only want the sample median, or Q1 and Q3 as a single spread figure.

Scope

Note

Returns one or more empirical quantiles of a bounded finite numeric vector.

Non-goals

Does not compute confidence intervals or approximate/streaming quantiles
Does not weight observations or group by a second key

Properties

IdempotentRetry safeStreaming supportedFile input supportedRequires external service

Capabilities

analysismath

Cost & billing

Flat rate per invocation

MetercallsBillable onsuccessCost per call1 credit

File handling

Accepts file_refProduces file_refMax input2 MB

How we handle your data

Sensitive input, safe output

What this means

This skill may receive sensitive content, but it does not target sensitive data and returns only a structured non-sensitive result.

Squillify guarantees

Runs inside Squillify
This skill runs inside Squillify.
Payloads are not sent to an external service by this skill.
Squillify does not permanently store submitted payloads.
Telemetry records metadata only, not submitted content.
Submitted payloads are not used for training.
Submitted payloads are not reviewed by humans.
This skill does not target sensitive data.
The response does not contain submitted content.

Your responsibility

Squillify does not determine whether submitted content is sensitive. Your application is responsible for deciding what data it is allowed to submit. Your application is responsible for securing the response.

Read the Microskill Data Handling Policy

Input schema

Field	Type	Required	Description
values	array	Yes	Required 1 to 100000 finite numbers. One extra slot exists in the schema so the typed ITEM_LIMIT_EXCEEDED failure is reachable at 100001.
probabilities	array	Yes	Required 1 to 101 probabilities in [0, 1]. One extra schema slot makes the typed item limit reachable.
method	string	No	Interpolation method; omit it for LINEAR_R7.
nullPolicy	string	No	REJECT fails on any JSON null; OMIT drops nulls and reports omittedCount. Omit this field and we REJECT.

Output schema

Field	Type	Required	Description
quantiles	array	Yes	From 1 through 101 probability/value pairs, ordered by probability.
method	string	Yes	Applied interpolation method.
count	integer	Yes	Finite observations used.
omittedCount	integer	Yes	How many JSON null observations were dropped under OMIT; zero under REJECT.

API contract

POST /v1/execute

curl

curl -sS -X POST "$BASE/v1/execute" -H "Authorization: Bearer $KEY" -H 'Content-Type: application/json' -d '{"skillKey":"statistics.quantile","input":{"values":[1,2,3,4,5],"probabilities":[0,0.5,1]}}'

Integrations

TypeScript SDK

import { Squillify } from "@squillify/sdk";

const sq = new Squillify({ apiKey: process.env.SQUILLIFY_API_KEY });

const { output } = await sq.execute("statistics.quantile", {"values":[1,2,3,4,5],"probabilities":[0,0.5,1]});

Errors

Code	HTTP	Retryable	Description
VALIDATION_ERROR	400	No	The request payload failed schema validation.
UNAUTHORIZED	401	No	Missing or invalid API key.
SKILL_NOT_ACCESSIBLE	403	No	The API key is not granted access to this skill.
SKILL_NOT_AVAILABLE_FOR_PLAN	403	No	This skill is not included in your current plan.
PLAN_ELIGIBILITY_UNAVAILABLE	503	Yes	Plan eligibility could not be decided. Retry after backoff.
SKILL_NOT_FOUND	404	No	The requested skill or version does not exist.
TENANT_RATE_LIMITED	429	Yes	Request rate limit exceeded. Retry after backoff.
QUOTA_EXCEEDED	429	Yes	Plan quota exhausted. Retryable once the quota period resets.
EXECUTION_TIMEOUT	504	Yes	Execution exceeded the allowed time budget.
SERIES_INVALID	400	No	The request payload failed this skill's input validation.
ITEM_LIMIT_EXCEEDED	429	No	A size, quota, rate, or time limit was exceeded.

Other limits

Limit	Value
Recommended inline bytes	32 KiB

Limitations

Does not compute confidence intervals or approximate/streaming quantiles
Does not weight observations or group by a second key
Only the sample median (use statistics.median)
Q1, Q3 and their difference together (use statistics.interquartile_range)

How to call

POST /v1/execute (requires authentication)

Request bodyjson

{
  "skillKey": "statistics.quantile",
  "input": {
    "values": [
      1,
      2,
      3,
      4,
      5
    ],
    "probabilities": [
      0,
      0.5,
      1
    ]
  }
}

Examples

Type-7 endpoints and the sample median

Inputjson

{
  "values": [
    1,
    2,
    3,
    4,
    5
  ],
  "probabilities": [
    0,
    0.5,
    1
  ]
}

Expected outputjson

{
  "quantiles": [
    {
      "value": 1,
      "probability": 0
    },
    {
      "value": 3,
      "probability": 0.5
    },
    {
      "value": 5,
      "probability": 1
    }
  ],
  "omittedCount": 0,
  "count": 5,
  "method": "LINEAR_R7"
}

Tip

h = p × 4, so 0 and 1 are the min and max and 0.5 is the middle sample

Nearest half-to-even index on an even sample