Detail: Series: Accessor ValuesΒΆ
Overview: Series: Accessor Values
- Series.via_values.apply(func, *args, **kwargs)
- Series.via_values
Interface for applying functions to values (as arrays) in this container.
- InterfaceValues.apply(func, *args, **kwargs)[source]
>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c')) >>> s.via_values.apply(np.sin) <Series> <Index> a -0.5440211108893698 b 0.9092974268256817 c 0.9893582466233818 <<U1> <float64>
- Series.via_values.__array_ufunc__(ufunc, method, *args, **kwargs)
- Series.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, returning NumPy arrays.
>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c')) >>> np.sin(s.via_values) <Series> <Index> a -0.5440211108893698 b 0.9092974268256817 c 0.9893582466233818 <<U1> <float64>
- Series.via_values.__call__(*, consolidate_blocks, unify_blocks, dtype)
- Series.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 β Group adjacent same-typed arrays into 2D arrays.
unify_blocks β Group all arrays into single array, re-typing to an appropriate dtype.
dtype β specify a dtype to be used in conversion before consolidation or unification, and before function application.
>>> s = sf.Series((10, 2, 8), index=('a', 'b', 'c')) >>> np.sin(s.via_values(unify_blocks=True)) <Series> <Index> a -0.5440211108893698 b 0.9092974268256817 c 0.9893582466233818 <<U1> <float64>
Series: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Assignment | Selector | Iterator | Operator Binary | Operator Unary | Accessor Values | Accessor Datetime | Accessor String | Accessor Fill Value | Accessor Regular Expression | Accessor Hashlib