Detail: Batch: Accessor Transpose
Overview: Batch: Accessor Transpose
- Batch.via_T.via_fill_value(fill_value)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.via_fill_value(fill_value)[source]
Interface for using binary operators and methods with a pre-defined fill value.
>>>
- Batch.via_T.__add__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__add__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T + s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p 10.0 8.0 1.0 i q -4.0 -5.0 -2.0 i r 0.5 8.5 9.5 i s 1.0 1.0 13.0 j p 1.0 2.0 1.0 j q 0.0 -1.0 -2.0 j r 0.5 2.5 2.5 j s 1.0 1.0 2.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__sub__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__sub__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T - s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p 10.0 8.0 1.0 i q 0.0 -1.0 2.0 i r -0.5 7.5 8.5 i s -1.0 -1.0 11.0 j p 1.0 2.0 1.0 j q 4.0 3.0 2.0 j r -0.5 1.5 1.5 j s -1.0 -1.0 0.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__mul__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__mul__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T * s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p 0.0 0.0 0.0 i q 4.0 6.0 -0.0 i r 0.0 4.0 4.5 i s 0.0 0.0 12.0 j p 0.0 0.0 0.0 j q -4.0 -2.0 -0.0 j r 0.0 1.0 1.0 j s 0.0 0.0 1.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__truediv__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__truediv__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T / s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p inf inf inf i q 1.0 1.5 -0.0 i r 0.0 16.0 18.0 i s 0.0 0.0 12.0 j p inf inf inf j q -1.0 -0.5 -0.0 j r 0.0 4.0 4.0 j s 0.0 0.0 1.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__floordiv__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__floordiv__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T // s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p inf inf inf i q 1.0 1.0 -0.0 i r 0.0 16.0 18.0 i s 0.0 0.0 12.0 j p inf inf inf j q -1.0 -1.0 -0.0 j r 0.0 4.0 4.0 j s 0.0 0.0 1.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__mod__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__mod__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T % s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p nan nan nan i q -0.0 -1.0 -0.0 i r 0.0 0.0 0.0 i s 0.0 0.0 0.0 j p nan nan nan j q -0.0 -1.0 -0.0 j r 0.0 0.0 0.0 j s 0.0 0.0 0.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__pow__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__pow__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T ** s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p 1.0 1.0 1.0 i q 0.25 0.1111111111111111 inf i r 0.0 2.8284271247461903 3.0 i s 0.0 0.0 12.0 j p 1.0 1.0 1.0 j q 0.25 1.0 inf j r 0.0 1.4142135623730951 1.4142135623730951 j s 0.0 0.0 1.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__lshift__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__lshift__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 3, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T << s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p 10 8 1 i q 0 0 0 i r 0 64 72 i s 0 0 24 j p 1 2 1 j q 0 0 0 j r 0 16 16 j s 0 0 2 <<U1> <<U1> <int64> <int64> <int64>
- Batch.via_T.__rshift__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__rshift__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 3, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T >> s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p 10 8 1 i q -1 -1 0 i r 0 1 1 i s 0 0 6 j p 1 2 1 j q 0 0 0 j r 0 0 0 j s 0 0 0 <<U1> <<U1> <int64> <int64> <int64>
- Batch.via_T.__and__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__and__(other)[source]
>>> bt = sf.Batch((('i', sf.Frame((np.arange(6).reshape(3,2) % 2).astype(bool), index=('p', 'q', 'r'), columns=('c', 'd'), name='y')), ('j', sf.Frame((np.arange(6).reshape(3,2) % 3).astype(bool), index=('p', 'q', 'r'), columns=('c', 'd'), name='w')))) >>> s = sf.Series((False, True, True), index=('p', 'q', 'r')) >>> (bt.via_T & s).to_frame() <Frame> <Index> c d <<U1> <IndexHierarchy> i p False False i q False True i r False True j p False False j q True False j r True True <<U1> <<U1> <bool> <bool>
- Batch.via_T.__xor__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__xor__(other)[source]
>>> bt = sf.Batch((('i', sf.Frame((np.arange(6).reshape(3,2) % 2).astype(bool), index=('p', 'q', 'r'), columns=('c', 'd'), name='y')), ('j', sf.Frame((np.arange(6).reshape(3,2) % 3).astype(bool), index=('p', 'q', 'r'), columns=('c', 'd'), name='w')))) >>> s = sf.Series((False, True, True), index=('p', 'q', 'r')) >>> (bt.via_T ^ s).to_frame() <Frame> <Index> c d <<U1> <IndexHierarchy> i p False True i q True False i r True False j p False True j q False True j r False False <<U1> <<U1> <bool> <bool>
- Batch.via_T.__or__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__or__(other)[source]
Return self|value.
>>> bt = sf.Batch((('i', sf.Frame((np.arange(6).reshape(3,2) % 2).astype(bool), index=('p', 'q', 'r'), columns=('c', 'd'), name='y')), ('j', sf.Frame((np.arange(6).reshape(3,2) % 3).astype(bool), index=('p', 'q', 'r'), columns=('c', 'd'), name='w')))) >>> s = sf.Series((False, True, True), index=('p', 'q', 'r')) >>> (bt.via_T | s).to_frame() <Frame> <Index> c d <<U1> <IndexHierarchy> i p False True i q True True i r True True j p False True j q True True j r True True <<U1> <<U1> <bool> <bool>
- Batch.via_T.__lt__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__lt__(other)[source]
Return self<value.
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T < s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p False False False i q False True False i r True False False i s True True False j p False False False j q False False False j r True False False j s True True False <<U1> <<U1> <bool> <bool> <bool>
- Batch.via_T.__le__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__le__(other)[source]
Return self<=value.
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T <= s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p False False False i q True True False i r True False False i s True True False j p False False False j q False False False j r True False False j s True True True <<U1> <<U1> <bool> <bool> <bool>
- Batch.via_T.__eq__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__eq__(other)[source]
Return self==value.
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T == s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p False False False i q True False False i r False False False i s False False False j p False False False j q False False False j r False False False j s False False True <<U1> <<U1> <bool> <bool> <bool>
- Batch.via_T.__ne__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__ne__(other)[source]
Return self!=value.
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T != s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p True True True i q False True True i r True True True i s True True True j p True True True j q True True True j r True True True j s True True False <<U1> <<U1> <bool> <bool> <bool>
- Batch.via_T.__gt__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__gt__(other)[source]
Return self>value.
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T > s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p True True True i q False False True i r False True True i s False False True j p True True True j q True True True j r False True True j s False False False <<U1> <<U1> <bool> <bool> <bool>
- Batch.via_T.__ge__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__ge__(other)[source]
Return self>=value.
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T >= s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p True True True i q True False True i r False True True i s False False True j p True True True j q True True True j r False True True j s False False True <<U1> <<U1> <bool> <bool> <bool>
- Batch.via_T.__radd__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__radd__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T + s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p 10.0 8.0 1.0 i q -4.0 -5.0 -2.0 i r 0.5 8.5 9.5 i s 1.0 1.0 13.0 j p 1.0 2.0 1.0 j q 0.0 -1.0 -2.0 j r 0.5 2.5 2.5 j s 1.0 1.0 2.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__rsub__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__rsub__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T - s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p 10.0 8.0 1.0 i q 0.0 -1.0 2.0 i r -0.5 7.5 8.5 i s -1.0 -1.0 11.0 j p 1.0 2.0 1.0 j q 4.0 3.0 2.0 j r -0.5 1.5 1.5 j s -1.0 -1.0 0.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__rmul__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__rmul__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T * s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p 0.0 0.0 0.0 i q 4.0 6.0 -0.0 i r 0.0 4.0 4.5 i s 0.0 0.0 12.0 j p 0.0 0.0 0.0 j q -4.0 -2.0 -0.0 j r 0.0 1.0 1.0 j s 0.0 0.0 1.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__rtruediv__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__rtruediv__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T / s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p inf inf inf i q 1.0 1.5 -0.0 i r 0.0 16.0 18.0 i s 0.0 0.0 12.0 j p inf inf inf j q -1.0 -0.5 -0.0 j r 0.0 4.0 4.0 j s 0.0 0.0 1.0 <<U1> <<U1> <float64> <float64> <float64>
- Batch.via_T.__rfloordiv__(other)
- Batch.via_T
Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
- InterfaceBatchTranspose.__rfloordiv__(other)[source]
>>> bt = sf.Batch((('i', 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')), ('j', sf.Frame.from_fields(((1, 2, 0, 0), (2, 1, 2, 0), (1, 0, 2, 1)), index=('p', 'q', 'r', 's'), columns=('a', 'b', 'c'), name='x')))) >>> s = sf.Series((0, -2, 0.5, 1), index=('p', 'q', 'r', 's')) >>> (bt.via_T // s).to_frame() <Frame> <Index> a b c <<U1> <IndexHierarchy> i p inf inf inf i q 1.0 1.0 -0.0 i r 0.0 16.0 18.0 i s 0.0 0.0 12.0 j p inf inf inf j q -1.0 -1.0 -0.0 j r 0.0 4.0 4.0 j s 0.0 0.0 1.0 <<U1> <<U1> <float64> <float64> <float64>
Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Values | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression | Accessor Hashlib | Accessor Type Clinic