LogoLogo
AboutBlogLaunch app ↗
v0.23.x
v0.23.x
  • Get Started
  • Overview
  • Getting Access to Distributional
  • Install the Python SDK
  • Quickstart
  • Learning about Distributional
    • Distributional Concepts
    • Why We Test Data Distributions
    • The Flow of Data
  • Using Distributional
    • Projects
    • Runs
      • Reporting Runs
      • Setting a Baseline Run
    • Metrics
    • Tests
      • Creating Tests
        • Using Filters in Tests
        • Available Statistics and Assertions
      • Running Tests
      • Reviewing Tests
        • What Is a Similarity Index?
    • Notifications
    • Access Controls
      • Organization and Namespaces
      • Users and Permissions
      • Tokens
  • Platform
    • Sandbox
    • Self-hosted
      • Architecture
      • Deployment
        • Helm Chart
        • Terraform Module
      • Networking
      • OIDC Authentication
      • Data Security
  • Reference
    • Query Language
      • Functions
    • Python SDK
      • dbnl
      • dbnl.util
      • dbnl.experimental
      • Classes
      • Eval Module
        • Quick Start
        • dbnl.eval
        • dbnl.eval.metrics
        • Application Metric Sets
        • How-To / FAQ
        • LLM-as-judge and Embedding Metrics
        • RAG / Question Answer Example
      • Classes
  • CLI
  • Versions
    • Release Notes
Powered by GitBook

© 2025 Distributional, Inc. All Rights Reserved.

On this page
  • Statistics
  • Assertions

Was this helpful?

Export as PDF
  1. Using Distributional
  2. Tests
  3. Creating Tests

Available Statistics and Assertions

Statistics

Statistic
Description

absolute difference of max

-

absolute difference of mean

-

absolute difference of median

-

absolute difference of min

-

absolute difference of percentile

Requires percentage as a parameter.

absolute difference of standard deviation

-

absolute difference of sum

-

Category Rank Discrepancy

Computes the absolute difference in the proportion of the specified category between the experiment and baseline runs. The category is specified by its rank in the baseline run.

Requires rankas a parameter: can be one of [most_common, second_most_common, not_top_two].

Chi-squared stat, scaled

Kolmogorov-Smirnov stat, scaled

max

-

mean

-

median

-

min

-

mode

-

Null Count

Computes the number of None values in a column.

Null Percentage

Computes the fraction of None values in a column.

percentile

Requires percentage as a parameter.

scalar

signed difference of max

-

signed difference of mean

-

signed difference of median

-

signed difference of min

-

signed difference of percentile

Requires percentage as a parameter.

signed difference of standard deviation

-

signed difference of sum

-

standard deviation

-

sum

-

Assertions

Assertion

between

between or equal to

close to

equal to

greater than

greater than or equal to

less than

less than or equal to

not equal to

outside

outside or equal to

PreviousUsing Filters in TestsNextRunning Tests

Was this helpful?

Computes a scaled and normalized statistic between two nominal distributions.

Computes a scaled and normalized statistic between two ordinal distributions.

Special function for using in tests. Returns the input as a scalar value if it is a scalar and returns an error otherwise.

Chi-squared
Kolmogorov-Smirnov
scalars