pandera.engines.pandas_engine.ArrowDecimal128

class pandera.engines.pandas_engine.ArrowDecimal128(precision=28, scale=0, rounding=<factory>)

Semantic representation of a pyarrow.decimal128.

Attributes

auto_coerce	Whether to force coerce to be True in all cases
continuous	Whether the number data type is continuous.
exact	Whether the data type is an exact representation of a number.
precision	The number of significant digits that the decimal type can represent.
scale	The number of digits after the decimal point.
type	Native pandas dtype boxed by the data type.
rounding	The rounding mode supported by the Python decimal.Decimal class.

Methods

__init__(precision=28, scale=0, rounding=<factory>)

check(pandera_dtype, data_container=None)

Check that pandera DataType are equivalent.

Parameters:

• pandera_dtype (DataType) – Expected DataType.

• data_container (Union[Series, DataFrame, None]) – Data container, used by data types that require the actual data for validation.

Return type:

Union[bool, Iterable[bool]]

Returns:

boolean scalar or iterable of boolean scalars, indicating which elements passed the check.

coerce(data_container)

Pure coerce without catching exceptions.

Return type:

Union[Series, DataFrame]

coerce_value(value)

Coerce a value to a particular type.

Return type:

Any

classmethod from_parametrized_dtype(pyarrow_dtype)

try_coerce(data_container)

Coerce data container to the data type, raises a ParserError if the coercion fails :raises: ParserError: if coercion fails

Return type:

Union[Series, DataFrame]

__call__(data_container)

Coerce data container to the data type.