Detail: IndexMicrosecond: Constructor

IndexMicrosecond.__init__(labels, *, loc_is_iloc=False, name=<object object>)

Initializer.

Parameters:

labels – Iterable of hashable values to be used as the index labels. If strings, NumPy datetime conversions will be applied.
name – A hashable object to label the container.

>>> sf.IndexMicrosecond(('1517-04-01', '1517-12-31', '1517-06-30'))
<IndexMicrosecond>
1517-04-01T00:00:00.000000
1517-12-31T00:00:00.000000
1517-06-30T00:00:00.000000
<datetime64[us]>

classmethod IndexMicrosecond.from_labels(labels, *, name=None)

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

>>> sf.IndexMicrosecond.from_labels(('1517-04-01', '1517-12-31', '1517-06-30'))
<IndexMicrosecond>
1517-04-01T00:00:00.000000
1517-12-31T00:00:00.000000
1517-06-30T00:00:00.000000
<datetime64[us]>

classmethod IndexMicrosecond.from_pandas(value)

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

>>> ix = pd.Index(('1517-04-01', '1517-12-31', '1517-06-30'))
>>> sf.IndexMicrosecond.from_pandas(ix)
<Index>
1517-04-01
1517-12-31
1517-06-30
<object>