Detail: Series: Assignment

Series.assign[key](value, *, fill_value)

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
<Series>
<Index>
a        2
b        8
c        19
d        34
e        54
<<U1>    <int64>
>>> 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
<Series>
<Index>
a        2
b        8
c        19
d        34
e        54
<<U1>    <int64>
>>> 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
<Series>
<Index>
a        2
b        8
c        19
d        34
e        54
<<U1>    <int64>
>>> 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>