Basic example

Pandera Schema

python

from pandera import Column, DataFrameSchema, Index

basic_schema = DataFrameSchema(
    {
        "field1": Column(
            int, title="Field 1 Title", description="My field description"
        ),
    },
    index=Index(int),
    strict=True,
    coerce=True,
    description="First data model for testing purposes",
)

sphinx-pandera

pandera schema target.basic_schema.basic_schema

First data model for testing purposes

Schema Configuration:

• coerce = True

• ordered = False

• strict = True

column field1: int64, Field 1 Title

My field description

Constraints:

• nullable = False

• unique = False

• coerce = False

• required = True

rst

.. autopandera_schema:: target.basic_schema.basic_schema

NB: If you want to use markdown with myst-parser, use the eval-rst directive.

Pandera Model

python

import pandera as pa


class TestModel(pa.DataFrameModel):
    """
    First data model for testing purposes
    """

    field1: int = pa.Field(
        title="Field 1 Title",
        description="My field description",
    )

sphinx-pandera

pandera model target.basic_model.TestModel

First data model for testing purposes

column field1: int, Field 1 Title

My field description

Constraints:

• nullable = False

• unique = False

• coerce = False

• required = True

class Config

coerce: bool

coerce types of all schema components

ordered: bool

validate columns order

strict: StrictType

make sure all specified columns are in the validated dataframe - if "filter", removes columns not specified in the schema

rst

.. autopandera_model:: target.basic_model.TestModel

NB: If you want to use markdown with myst-parser, use the eval-rst directive.