Detail: Index: Constructor#

Overview: Index: Constructor

Index.__init__(labels, /, *, loc_is_iloc=False, name=<object object>, dtype=None, sort_status=SortStatus.UNKNOWN)[source]#

Initializer.

Parameters:

labels – An iterable of unique, hashable values, or another Index or IndexHierarchy, to be used as the labels of the index.
name – A hashable object to label the container.
loc_is_iloc – Optimization when a contiguous integer index is provided as labels. Generally only set by internal clients.
dtype – A value suitable for specyfying a NumPy dtype, such as a Python type (float), NumPy array protocol strings (‘f8’), or a dtype instance.

>>> sf.Index(('a', 'b', 'c', 'd', 'e'), name='x')
<Index: x>
a
b
c
d
e
<<U1>

classmethod Index.from_difference(*others)[source]#

Construct a new Index based on the difference with Index, containers, or NumPy arrays. Retains order.

>>> ix1 = sf.Index.from_labels(('a', 'b', 'c', 'd', 'e'), name='x')
>>> ix2 = sf.Index.from_labels(('c', 'd', 'e', 'f'), name='y')
>>> sf.Index.from_difference(ix1, ix2)
<Index>
a
b
<<U1>

classmethod Index.from_intersection(*others)[source]#

Construct a new Index based on the intersection with Index, containers, or NumPy arrays. Identical comparisons retain order.

>>> ix1 = sf.Index.from_labels(('a', 'b', 'c', 'd', 'e'), name='x')
>>> ix2 = sf.Index.from_labels(('c', 'd', 'e', 'f'), name='y')
>>> sf.Index.from_intersection(ix1, ix2)
<Index>
c
d
e
<<U1>

classmethod Index.from_labels(labels, /, *, name=None)[source]#

Construct an Index from an iterable of labels, where each label is a hashable. Provided for a compatible interface to IndexHierarchy.

>>> sf.Index.from_labels(('a', 'b', 'c', 'd', 'e'), name='x')
<Index: x>
a
b
c
d
e
<<U1>

classmethod Index.from_pandas(value, /)#

Given a Pandas index, return the appropriate IndexBase derived class.

>>> ix = pd.Index(('a', 'b', 'c', 'd', 'e'), name='x')
>>> sf.Index.from_pandas(ix)
<Index: x>
a
b
c
d
e
<object>

classmethod Index.from_union(*others)[source]#

Construct a new Index based on the union with Index, containers, or NumPy arrays. Identical comparisons retain order.

>>> ix1 = sf.Index.from_labels(('a', 'b', 'c', 'd', 'e'), name='x')
>>> ix2 = sf.Index.from_labels(('c', 'd', 'e', 'f'), name='y')
>>> sf.Index.from_union(ix1, ix2)
<Index>
a
b
c
d
e
f
<<U1>