Detail: Frame: Accessor Values
Overview: Frame: Accessor Values
- Frame.via_values.apply(func, *args, **kwargs)
- Frame.via_values
Interface for applying functions to values (as arrays) in this container.
- 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.
- InterfaceValues.apply(func, *args, **kwargs)[source]
>>> f = sf.Frame.from_fields(((10, -2, 0, 0), (8, -3, 8, 0), (1, 0, 9, 12)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x') >>> f <Frame: x> <Index> a b c <<U1> <Index> p 10 8 1 q -2 -3 0 r 0 8 9 s 0 0 12 <<U1> <int64> <int64> <int64> >>> f.via_values.apply(np.sin) <Frame: x> <Index> a b c <<U1> <Index> p -0.5440211108893698 0.9893582466233818 0.8414709848078965 q -0.9092974268256817 -0.1411200080598672 0.0 r 0.0 0.9893582466233818 0.4121184852417566 s 0.0 0.0 -0.5365729180004349 <<U1> <float64> <float64> <float64>
- Frame.via_values.__array_ufunc__(ufunc, method, *args, **kwargs)
- Frame.via_values
Interface for applying functions to values (as arrays) in this container.
- 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.
- InterfaceValues.__array_ufunc__(ufunc, method, *args, **kwargs)[source]
Support for applying NumPy functions directly on containers.
>>> f = sf.Frame.from_fields(((10, -2, 0, 0), (8, -3, 8, 0), (1, 0, 9, 12)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x') >>> f <Frame: x> <Index> a b c <<U1> <Index> p 10 8 1 q -2 -3 0 r 0 8 9 s 0 0 12 <<U1> <int64> <int64> <int64> >>> np.sin(f.via_values) <Frame: x> <Index> a b c <<U1> <Index> p -0.5440211108893698 0.9893582466233818 0.8414709848078965 q -0.9092974268256817 -0.1411200080598672 0.0 r 0.0 0.9893582466233818 0.4121184852417566 s 0.0 0.0 -0.5365729180004349 <<U1> <float64> <float64> <float64>
- Frame.via_values.__call__(*, consolidate_blocks, unify_blocks, dtype)
- Frame.via_values
Interface for applying functions to values (as arrays) in this container.
- 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.
- 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.
>>> f = sf.Frame.from_fields(((10, -2, 0, 0), (8, -3, 8, 0), (1, 0, 9, 12)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x') >>> f <Frame: x> <Index> a b c <<U1> <Index> p 10 8 1 q -2 -3 0 r 0 8 9 s 0 0 12 <<U1> <int64> <int64> <int64> >>> np.sin(f.via_values(unify_blocks=True)) <Frame: x> <Index> a b c <<U1> <Index> p -0.5440211108893698 0.9893582466233818 0.8414709848078965 q -0.9092974268256817 -0.1411200080598672 0.0 r 0.0 0.9893582466233818 0.4121184852417566 s 0.0 0.0 -0.5365729180004349 <<U1> <float64> <float64> <float64>
Frame: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Assignment | Selector | Iterator | Operator Binary | Operator Unary | Accessor Values | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression | Accessor Hashlib | Accessor Type Clinic