Detail: IndexYear: Accessor Values

IndexYear.via_values.apply(func, *args, **kwargs)

IndexYear.via_values: Interface for applying functions to values (as arrays) in this container.

InterfaceValues.apply(func, *args, **kwargs)[source]

>>> ix = sf.IndexYear(('1517', '1520', '1518'))
>>> ix
<IndexYear>
1517
1520
1518
<datetime64[Y]>
>>> ix.via_values.apply(np.sin)
TypeError("ufunc 'sin' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''")

IndexYear.via_values.__array_ufunc__(ufunc, method, *args, **kwargs)

IndexYear.via_values: Interface for applying functions to values (as arrays) in this container.

InterfaceValues.__array_ufunc__(ufunc, method, *args, **kwargs)[source]: Support for applying NumPy functions directly on containers.

>>> ix = sf.IndexYear(('1517', '1520', '1518'))
>>> ix
<IndexYear>
1517
1520
1518
<datetime64[Y]>
>>> np.sin(ix.via_values)
TypeError("ufunc 'sin' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''")

IndexYear.via_values.__call__(*, consolidate_blocks, unify_blocks, dtype)

IndexYear.via_values: Interface for applying functions to values (as arrays) in this container.

InterfaceValues.__call__(*, consolidate_blocks=False, unify_blocks=False, dtype=None)[source]

Parameters:

consolidate_blocks – Group adjacent same-typed arrays into 2D arrays.
unify_blocks – Group all arrays into single array, re-typing to an appropriate dtype.
dtype – specify a dtype to be used in conversion before consolidation or unification, and before function application.

>>> ix = sf.IndexYear(('1517', '1520', '1518'))
>>> ix
<IndexYear>
1517
1520
1518
<datetime64[Y]>
>>> np.sin(ix.via_values(unify_blocks=True))
TypeError("ufunc 'sin' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''")