class_docstr: Term for extracting a single column of a another term's output.
  
  Parameters
  ----------
  term : catalyst.pipeline.term.Term
      The term from which to extract a column of data.
  asset : catalyst.assets.Asset
      The asset corresponding to the column of `term` to be extracted.
  
  Notes
  -----
  Users should rarely construct instances of `Slice` directly. Instead, they
  should construct instances via indexing, e.g. `MyFactor()[Asset(24)]`.
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code: def _init(self, asset, *args, **kwargs):
      self._asset = asset
      return super(Slice, self)._init(*args, **kwargs)
  
imports: from abc import ABCMeta, abstractproperty
  from bisect import insort
  from collections import Mapping
  from weakref import WeakValueDictionary
  from numpy import array, dtype, ndarray, searchsorted
  from six import with_metaclass
  from catalyst.assets import Asset
  from catalyst.errors import DTypeNotSpecified, InvalidOutputName, NonExistentAssetInTimeFrame, NonSliceableTerm, NonWindowSafeInput, NotDType, TermInputsNotSpecified, TermOutputsEmpty, UnsupportedDType, WindowLengthNotSpecified
  from catalyst.lib.adjusted_array import can_represent_dtype
  from catalyst.lib.labelarray import LabelArray
  from catalyst.utils.input_validation import expect_types
  from catalyst.utils.memoize import lazyval
  from catalyst.utils.numpy_utils import bool_dtype, categorical_dtype, datetime64ns_dtype, default_missing_value_for_dtype
  from catalyst.utils.sharedoc import templated_docstring, PIPELINE_ALIAS_NAME_DOC, PIPELINE_DOWNSAMPLING_FREQUENCY_DOC
  from .downsample_helpers import expect_downsample_frequency
  from .sentinels import NotSpecified
label_desc: Use image node_id 3 for calling the Slice obj's underlying member method code with example usage: obj._init(asset) and returns: super