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STATISTICS

variation

Compute the coefficient of variation.

Example of usage

Python API reference included; executable data demonstration pending review.

Usage / limitations

+Use when: Summarise measurements and uncertainty.

−Limitations: Check input requirements, mathematical assumptions and version-specific behaviour before using.

Mathematical formula

See method documentation: implementation and assumptions vary.
Sample dataShow 
{
  "variable": "patient_wait_times",
  "domain": "Hospital outpatient waiting-time analysis",
  "feature_names": [
    "wait_minutes"
  ],
  "records": [
    {
      "wait_minutes": 12
    },
    {
      "wait_minutes": 16
    },
    {
      "wait_minutes": 18
    },
    {
      "wait_minutes": 20
    },
    {
      "wait_minutes": 24
    },
    {
      "wait_minutes": 30
    },
    {
      "wait_minutes": 34
    },
    {
      "wait_minutes": 40
    }
  ]
}

Code example (Python)

# DataLens.ai example — variation
# Domain: hospital outpatient waiting-time analysis.
# Sample data are included by Copy input + code + test.
import numpy as np
from scipy.stats import variation

# Extract named waiting-time observations into a numeric array.
values = np.array([row["wait_minutes"] for row in patient_wait_times["records"]], dtype=float)

# Apply this statistical method to the observations.
result = variation(values)

# Verify the calculated statistic against a mathematical property.
assert np.isclose(result, np.std(values)/np.mean(values))
print("Expected output verified")