Distribution

Overview

The distribution tool returns percentile-style distributions for supported metrics. Use it to analyze ranges, percentiles, and the spread of a metric rather than a single aggregate value.

For example, instead of viewing only the median salary, you can see how salaries are distributed across different percentile ranges.

Common Use Cases

Use the distribution tool to answer questions such as:

Use Case	Example
Salary spread	What is the salary distribution for a specific occupation or region?
Wage distribution	How are estimated wages distributed across a workforce segment?
Occupational earnings	What is the occupational earnings distribution in Core LMI?
Compensation analysis	Understand salary ranges and percentiles within a market.
Experience analysis	Analyze how experience requirements vary across job postings.
Earnings benchmarking	Compare occupational earnings across regions, industries, or occupations.

Supported Datasets

The distribution tool supports the following datasets.

Dataset	Supported	Notes
Job Posting	Yes	Requires a `time` filter.
Profile	Yes	Requires at least one extra metric.

Inputs

The tool accepts the following inputs.

Input	Description
`dataset`	The dataset to analyze.
`filter`	Filters are used to narrow the results.
`domainMetric`	The metric whose distribution will be analysed.
`extraMetrics`	Additional metrics were returned with distribution buckets where supported.
`percentiles`	Percentiles to return where supported by the dataset contract.

Supported domain Metrics.

Dataset	Domain metrics
`job_postings`	`postings.salary`, `postings.posting_duration`, `postings.min_years_experience`, `postings.max_years_experience`
`profiles`	`profiles.estimated_wage`

Select a domain metric based on the type of distribution you want to analyze. For example, you can analyze salary ranges, wage distributions, earnings distributions, or experience requirements depending on the selected dataset.

Example Request

{
  "dataset": "job_postings",
  "filter": {
    "time": {
      "level": 1,
      "values": {
        "start": "2024-01",
        "end": "2024-12",
        "postingType": "posted"
      }
    }
  },
  "domainMetric": "postings.salary",
  "extraMetrics": [
    "postings.unique_postings",
    "postings.median_salary"
  ],
  "percentiles": [10, 25, 50, 75, 90]
}

Outputs

The response returns distribution data for the selected metric.

Dataset	Output
`job_postings`	`domain` with `min` and `max`, plus `buckets` containing `key`, `value`, and `metrics`.
`profiles`	`domain` with `min` and `max`, plus `buckets` containing `key`, `value`, and `metrics`.

Depending on the dataset, the response results help you understand how values are distributed across a market rather than relying on a single average or median.

Example Response

{
  "domain": {
    "min": 45000,
    "max": 180000
  },
  "buckets": [
    {
      "key": "p50",
      "value": 95000,
      "metrics": {
        "postings.unique_postings": 620,
        "postings.median_salary": 95000
      }
    }
  ]
}