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Represents a single column in a model schema with its metadata and constraints. A Column defines the structure and properties of a data column that will be used in a Fiddler model. It includes information about the column’s data type, value ranges, categorical values, binning configuration, and other metadata necessary for proper data validation and monitoring. This class is used within ModelSchema to define the complete structure of data that a model expects to receive.

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Examples

Creating a numeric column: 
column = Column(
    name="age",
    data_type=DataType.INTEGER,
    min=0,
    max=120
)
Creating a categorical column: 
column = Column(
    name="category",
    data_type=DataType.CATEGORY,
    categories=["A", "B", "C"]
)
Creating a vector column: 
column = Column(
    name="embedding",
    data_type=DataType.VECTOR,
    n_dimensions=128
)

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name

Column name provided by the customer

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data_type

Data type of the column

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min

Min value of integer/float column

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max

Max value of integer/float column

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categories

List of unique values of a categorical column

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bins

Bins of integer/float column

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replace_with_nulls

Replace the list of given values to NULL if found in the events data

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model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

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n_dimensions

Number of dimensions of a vector column