column_anomalies

models:
  - name: this_is_a_model
    tests:
      - elementary.column_anomalies:
          column_anomalies:
            - null_count
            - missing_count
            - average

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column_anomalies: [column monitors list]

Select which monitors to activate as part of the test.

Default: default monitors
Relevant tests: all_columns_anomalies, column_anomalies
Configuration level: test

models:
  - name: this_is_a_model
    tests:
      - elementary.column_anomalies:
          column_anomalies:
            - null_count
            - missing_count
            - average

Supported column monitors

Default monitors by type:

Data quality metric	Column Type
`null_count`	any
`null_percent`	any
`min_length`	string
`max_length`	string
`average_length`	string
`missing_count`	string
`missing_percent`	string
`min`	numeric
`max`	numeric
`average`	numeric
`zero_count`	numeric
`zero_percent`	numeric
`standard_deviation`	numeric
`variance`	numeric

Opt-in monitors by type:

Data quality metric	Column Type
`sum`	numeric

models:
  - name: this_is_a_model
    tests:
      - elementary.column_anomalies:
          column_anomalies:
            - null_count
            - missing_count
            - average

models:
  - name: this_is_a_model
    tests:
      - elementary.column_anomalies:
          column_anomalies:
            - null_count
            - missing_count
            - average

Generate your anomaly test with Elementary AI

Let our Slack chatbot create the anomaly test you need.

column_anomalies: [column monitors list]

Select which monitors to activate as part of the test.

Default: default monitors
Relevant tests: all_columns_anomalies, column_anomalies
Configuration level: test

models:
  - name: this_is_a_model
    tests:
      - elementary.column_anomalies:
          column_anomalies:
            - null_count
            - missing_count
            - average

Supported column monitors

Default monitors by type:

Data quality metric	Column Type
`null_count`	any
`null_percent`	any
`min_length`	string
`max_length`	string
`average_length`	string
`missing_count`	string
`missing_percent`	string
`min`	numeric
`max`	numeric
`average`	numeric
`zero_count`	numeric
`zero_percent`	numeric
`standard_deviation`	numeric
`variance`	numeric

Opt-in monitors by type:

Data quality metric	Column Type
`sum`	numeric

models:
  - name: this_is_a_model
    tests:
      - elementary.column_anomalies:
          column_anomalies:
            - null_count
            - missing_count
            - average

Generate your anomaly test with Elementary AI

Supported column monitors

Elementary OSS

Quickstart

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Configuration & usage

Deployment

Integrations

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Release Notes

column_anomalies

Generate your anomaly test with Elementary AI

Supported column monitors

Generate your anomaly test with Elementary AI

​Supported column monitors

Elementary OSS

Quickstart

Guides

Configuration & usage

Deployment

Integrations

Community & Support

Release Notes

Generate your anomaly test with Elementary AI

​Supported column monitors

Supported column monitors

Supported column monitors