Detail: Series: Assignment¶
- Series.assign[key](value, *, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.__call__(value, *, fill_value=nan)[source]
Assign the
value
in the position specified by the selector. The name attribute is propagated to the returned container.- Parameters:
value – Value to assign, which can be a
Series
, np.ndarray, or element.*. –
fill_value – If the
value
parameter has to be reindexed, this element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s.assign['c']('x') <Series> <Index> a 2 b 8 c x d 34 e 54 <<U1> <object> >>> s.assign['c':]('x') <Series> <Index> a 2 b 8 c x d x e x <<U1> <object> >>> s.assign[['a', 'd']](('x', 'y')) <Series> <Index> a x b 8 c 19 d y e 54 <<U1> <object>
- Series.assign[key].apply(func, *, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.apply(func, *, fill_value=nan)[source]
Provide a function to apply to the assignment target, and use that as the assignment value.
- Parameters:
func – A function to apply to the assignment target.
*. –
fill_value – If the function does not produce a container with a matching index, the element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64> >>> s.assign['c':].apply(lambda s: s / 100) <Series> <Index> a 2.0 b 8.0 c 0.19 d 0.34 e 0.54 <<U1> <float64>
- Series.assign[key].apply_element(func, *, dtype, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.apply_element(func, *, dtype=None, fill_value=nan)[source]
Provide a function to apply to each element in the assignment target, and use that as the assignment value.
- Parameters:
func – A function to apply to the assignment target.
* –
fill_value – If the function does not produce a container with a matching index, the element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64> >>> s.assign['b':].apply_element(lambda e: e if e < 10 else f'--{e}--') <Series> <Index> a 2 b 8 c --19-- d --34-- e --54-- <<U1> <object>
- Series.assign[key].apply_element_items(func, *, dtype, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.apply_element_items(func, *, dtype=None, fill_value=nan)[source]
Provide a function, taking pairs of label, element, to apply to each element in the assignment target, and use that as the assignment value.
- Parameters:
func – A function, taking pairs of label, element, to apply to the assignment target.
* –
fill_value – If the function does not produce a container with a matching index, the element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64> >>> s.assign['b':].apply_element_items(lambda l, e: e if l == 'c' else f'--{e}--') <Series> <Index> a 2 b --8-- c 19 d --34-- e --54-- <<U1> <object>
- Series.assign.iloc[key](value, *, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.__call__(value, *, fill_value=nan)[source]
Assign the
value
in the position specified by the selector. The name attribute is propagated to the returned container.- Parameters:
value – Value to assign, which can be a
Series
, np.ndarray, or element.*. –
fill_value – If the
value
parameter has to be reindexed, this element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s.assign.iloc[2]('x') <Series> <Index> a 2 b 8 c x d 34 e 54 <<U1> <object> >>> s.assign.iloc[2:]('x') <Series> <Index> a 2 b 8 c x d x e x <<U1> <object> >>> s.assign.iloc[[0, 4]](('x', 'y')) <Series> <Index> a x b 8 c 19 d 34 e y <<U1> <object>
- Series.assign.iloc[key].apply(func, *, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.apply(func, *, fill_value=nan)[source]
Provide a function to apply to the assignment target, and use that as the assignment value.
- Parameters:
func – A function to apply to the assignment target.
*. –
fill_value – If the function does not produce a container with a matching index, the element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64> >>> s.assign.iloc[2:].apply(lambda s: s / 100) <Series> <Index> a 2.0 b 8.0 c 0.19 d 0.34 e 0.54 <<U1> <float64>
- Series.assign.iloc[key].apply_element(func, *, dtype, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.apply_element(func, *, dtype=None, fill_value=nan)[source]
Provide a function to apply to each element in the assignment target, and use that as the assignment value.
- Parameters:
func – A function to apply to the assignment target.
* –
fill_value – If the function does not produce a container with a matching index, the element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64> >>> s.assign.iloc[2:].apply_element(lambda e: e / 100 if e < 10 else e) <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64>
- Series.assign.iloc[key].apply_element_items(func, *, dtype, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.apply_element_items(func, *, dtype=None, fill_value=nan)[source]
Provide a function, taking pairs of label, element, to apply to each element in the assignment target, and use that as the assignment value.
- Parameters:
func – A function, taking pairs of label, element, to apply to the assignment target.
* –
fill_value – If the function does not produce a container with a matching index, the element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64> >>> s.assign.iloc[2:].apply_element_items(lambda l, e: e if l == 'c' else f'--{e}--') <Series> <Index> a 2 b 8 c 19 d --34-- e --54-- <<U1> <object>
- Series.assign.loc[key](value, *, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.__call__(value, *, fill_value=nan)[source]
Assign the
value
in the position specified by the selector. The name attribute is propagated to the returned container.- Parameters:
value – Value to assign, which can be a
Series
, np.ndarray, or element.*. –
fill_value – If the
value
parameter has to be reindexed, this element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s.assign.loc['c']('x') <Series> <Index> a 2 b 8 c x d 34 e 54 <<U1> <object> >>> s.assign.loc['c':]('x') <Series> <Index> a 2 b 8 c x d x e x <<U1> <object> >>> s.assign.loc[['a', 'd']](('x', 'y')) <Series> <Index> a x b 8 c 19 d y e 54 <<U1> <object>
- Series.assign.loc[key].apply(func, *, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.apply(func, *, fill_value=nan)[source]
Provide a function to apply to the assignment target, and use that as the assignment value.
- Parameters:
func – A function to apply to the assignment target.
*. –
fill_value – If the function does not produce a container with a matching index, the element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64> >>> s.assign.loc['c':].apply(lambda s: s / 100) <Series> <Index> a 2.0 b 8.0 c 0.19 d 0.34 e 0.54 <<U1> <float64>
- Series.assign.loc[key].apply_element(func, *, dtype, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.apply_element(func, *, dtype=None, fill_value=nan)[source]
Provide a function to apply to each element in the assignment target, and use that as the assignment value.
- Parameters:
func – A function to apply to the assignment target.
* –
fill_value – If the function does not produce a container with a matching index, the element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64> >>> s.assign.loc['c':].apply_element(lambda e: e / 100 if e < 10 else e) <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64>
- Series.assign.loc[key].apply_element_items(func, *, dtype, fill_value)
- Series.assign
Interface for doing assignment-like selection and replacement.
- SeriesAssign.apply_element_items(func, *, dtype=None, fill_value=nan)[source]
Provide a function, taking pairs of label, element, to apply to each element in the assignment target, and use that as the assignment value.
- Parameters:
func – A function, taking pairs of label, element, to apply to the assignment target.
* –
fill_value – If the function does not produce a container with a matching index, the element will be used to fill newly created elements.
>>> s = sf.Series((2, 8, 19, 34, 54), index=('a', 'b', 'c', 'd', 'e')) >>> s <Series> <Index> a 2 b 8 c 19 d 34 e 54 <<U1> <int64> >>> s.assign.loc['c':].apply_element_items(lambda l, e: e / 100 if l == 'c' else e) <Series> <Index> a 2.0 b 8.0 c 0.19 d 34.0 e 54.0 <<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