Detail: IndexMicrosecond: Dictionary-Like

Overview: IndexMicrosecond: Dictionary-Like

IndexMicrosecond.__contains__(value)

Return True if value in the labels. Will only return True for an exact match to the type of dates stored within.

>>> ix = sf.IndexMicrosecond(('1517-04-01', '1517-12-31', '1517-06-30'))
>>> ix
<IndexMicrosecond>
1517-04-01T00:00:00.000000
1517-12-31T00:00:00.000000
1517-06-30T00:00:00.000000
<datetime64[us]>
>>> ix.__contains__('a')
ValueError('Error parsing datetime string "a" at position 0')
>>> ix = sf.IndexMicrosecond(('1517-04-01', '1517-12-31', '1517-06-30'))
>>> ix
<IndexMicrosecond>
1517-04-01T00:00:00.000000
1517-12-31T00:00:00.000000
1517-06-30T00:00:00.000000
<datetime64[us]>
>>> ix.__contains__('1517-06-30')
False

IndexMicrosecond.__iter__()

Iterate over labels.

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

IndexMicrosecond.__reversed__()

Returns a reverse iterator on the index labels.

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

IndexMicrosecond.values

A 1D NumPy array of the values in the Index. This array will have the same dtype as the container.

>>> ix = sf.IndexMicrosecond(('1517-04-01', '1517-12-31', '1517-06-30'))
>>> ix
<IndexMicrosecond>
1517-04-01T00:00:00.000000
1517-12-31T00:00:00.000000
1517-06-30T00:00:00.000000
<datetime64[us]>
>>> ix.values_at_depth(0)
['1517-04-01T00:00:00.000000' '1517-12-31T00:00:00.000000'
 '1517-06-30T00:00:00.000000']