Detail: IndexNanosecond: Iterator

Overview: IndexNanosecond: Iterator

IndexNanosecond.iter_label(depth_level)
iter_label
>>> ix = sf.IndexNanosecond(('1789-05-05', '1789-12-31', '1799-11-09'))
>>> ix
<IndexNanosecond>
1789-05-05T00:00:00.000000000
1789-12-31T00:00:00.000000000
1799-11-09T00:00:00.000000000
<datetime64[ns]>
>>> tuple(ix.iter_label())
(numpy.datetime64('1789-05-05T00:00:00.000000000'), numpy.datetime64('1789-12-31T00:00:00.000000000'), numpy.datetime64('1799-11-09T00:00:00.000000000'))
IndexNanosecond.iter_label(depth_level).apply(func, *, dtype, name, index_constructor, columns_constructor)
iter_label
IterNodeDelegate.apply(func, *, dtype=None, name=None, index_constructor=None, columns_constructor=None)[source]

Apply a function to each value. Returns a new container.

Parameters:
  • func – A function that takes a value.

  • dtype – A value suitable for specyfying a NumPy dtype, such as a Python type (float), NumPy array protocol strings (‘f8’), or a dtype instance.

>>> ix = sf.IndexNanosecond(('1789-05-05', '1789-12-31', '1799-11-09'))
>>> ix
<IndexNanosecond>
1789-05-05T00:00:00.000000000
1789-12-31T00:00:00.000000000
1799-11-09T00:00:00.000000000
<datetime64[ns]>
>>> ix.iter_label().apply(lambda l: l.astype('<M8[ms]').astype(object).year)
[1789 1789 1799]
IndexNanosecond.iter_label(depth_level).apply_iter(func)
iter_label
IterNodeDelegate.apply_iter(func)[source]

Apply a function to each value. A generator of resulting values.

Parameters:

func – A function that takes a value.

Yields:

Values after function application.

>>> ix = sf.IndexNanosecond(('1789-05-05', '1789-12-31', '1799-11-09'))
>>> ix
<IndexNanosecond>
1789-05-05T00:00:00.000000000
1789-12-31T00:00:00.000000000
1799-11-09T00:00:00.000000000
<datetime64[ns]>
>>> tuple(ix.iter_label().apply_iter(lambda l: l.astype('<M8[ms]').astype(object)))
(datetime.datetime(1789, 5, 5, 0, 0), datetime.datetime(1789, 12, 31, 0, 0), datetime.datetime(1799, 11, 9, 0, 0))
IndexNanosecond.iter_label(depth_level).apply_iter_items(func)
iter_label
IterNodeDelegate.apply_iter_items(func)[source]

Apply a function to each value. A generator of resulting key, value pairs.

Parameters:

func – A function that takes a value.

Yields:

Pairs of label, value after function application.

>>> ix = sf.IndexNanosecond(('1789-05-05', '1789-12-31', '1799-11-09'))
>>> ix
<IndexNanosecond>
1789-05-05T00:00:00.000000000
1789-12-31T00:00:00.000000000
1799-11-09T00:00:00.000000000
<datetime64[ns]>
>>> tuple(ix.iter_label().apply_iter_items(lambda l: l.astype('<M8[ms]').astype(object)))
((0, datetime.datetime(1789, 5, 5, 0, 0)), (1, datetime.datetime(1789, 12, 31, 0, 0)), (2, datetime.datetime(1799, 11, 9, 0, 0)))
IndexNanosecond.iter_label(depth_level).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)
iter_label
IterNodeDelegate.apply_pool(func, *, dtype=None, name=None, index_constructor=None, max_workers=None, chunksize=1, use_threads=False)[source]

Apply a function to each value. Employ parallel processing with either the ProcessPoolExecutor or ThreadPoolExecutor.

Parameters:
  • func – A function that takes a value.

  • *

  • dtype – A value suitable for specyfying a NumPy dtype, such as a Python type (float), NumPy array protocol strings (‘f8’), or a dtype instance.

  • name – A hashable object to label the container.

  • max_workers – Number of parallel executors, as passed to the Thread- or ProcessPoolExecutor; None defaults to the max number of machine processes.

  • chunksize – Units of work per executor, as passed to the Thread- or ProcessPoolExecutor.

  • use_threads – Use the ThreadPoolExecutor instead of the ProcessPoolExecutor.

>>> ix = sf.IndexNanosecond(('1789-05-05', '1789-12-31', '1799-11-09'))
>>> ix
<IndexNanosecond>
1789-05-05T00:00:00.000000000
1789-12-31T00:00:00.000000000
1799-11-09T00:00:00.000000000
<datetime64[ns]>
>>> ix.iter_label().apply_pool(lambda l: l.astype('<M8[ms]').astype(object).month, use_threads=True)
[ 5 12 11]

IndexNanosecond: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Iterator | Operator Binary | Operator Unary | Accessor Values | Accessor Datetime | Accessor String | Accessor Regular Expression | Accessor Hashlib | Accessor Type Clinic