> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fiddler.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Column

> Represents a single column in a model schema with its metadata and constraints.

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.

## Examples

Creating a numeric column:

```python theme={null}
column = Column(
    name="age",
    data_type=DataType.INTEGER,
    min=0,
    max=120
)
```

Creating a categorical column:

```python theme={null}
column = Column(
    name="category",
    data_type=DataType.CATEGORY,
    categories=["A", "B", "C"]
)
```

Creating a vector column:

```python theme={null}
column = Column(
    name="embedding",
    data_type=DataType.VECTOR,
    n_dimensions=128
)
```

## name

Column name provided by the customer

## data\_type

Data type of the column

## min

Min value of integer/float column

## max

Max value of integer/float column

## categories

List of unique values of a categorical column

## bins

Bins of integer/float column

## replace\_with\_nulls

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

## model\_config

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

## n\_dimensions

Number of dimensions of a vector column