pyarrow.MonthDayNanoIntervalScalar#

class pyarrow.MonthDayNanoIntervalScalar#

Bases: Scalar

Concrete class for month, day, nanosecond interval scalars.

__init__(*args, **kwargs)#

Methods

__init__(*args,**kwargs)
as_py(self,*[,maps_as_pydicts])	Return this value as a pyarrow.MonthDayNano.
cast(self[,target_type,safe,options,...])	Cast scalar value to another data type.
equals(self,Scalarother)
validate(self,*[,full])	Perform validation checks.

Attributes

is_valid	Holds a valid (non-null) value.
type	Data type of the Scalar object.
value	Same as self.as_py()

as_py(self, *, maps_as_pydicts=None)#

Return this value as a pyarrow.MonthDayNano.

Parameters:

maps_as_pydictsstr, optional, default None

Valid values are None, lossy, or strict. This parameter is ignored for non-nested Scalars.

cast(self, target_type=None, safe=None, options=None, memory_pool=None)#

Cast scalar value to another data type.

See pyarrow.compute.cast() for usage.

Parameters:

target_typeDataType, default None

Type to cast scalar to.

safebool, default True

Whether to check for conversion errors such as overflow.

optionsCastOptions, default None

Additional checks pass by CastOptions

memory_poolMemoryPool, optional

memory pool to use for allocations during function execution.

Returns:

scalarA Scalar of the given target data type.

equals(self, Scalar other)#

Parameters:

otherpyarrow.Scalar

Returns:

bool

is_valid#

Holds a valid (non-null) value.

type#

Data type of the Scalar object.

validate(self, *, full=False)#

Perform validation checks. An exception is raised if validation fails.

By default only cheap validation checks are run. Pass full=True for thorough validation checks (potentially O(n)).

Parameters:

fullbool, default False

If True, run expensive checks, otherwise cheap checks only.

Raises:

ArrowInvalid

value#

Same as self.as_py()