code: def expected_latest(self, column, slice_):
      loader = self.seeded_random_loader
      index = self.trading_days[slice_]
      columns = self.assets
      values = loader.values(
          column.dtype, self.trading_days, self.sids
      )[slice_]
  
      if column.dtype.kind in ("O", "S", "U"):
          # For string columns, we expect a categorical in the output.
          return LabelArray(
              values,
              missing_value=column.missing_value,
          ).as_categorical_frame(
              index=index,
              columns=columns,
          )
  
      return DataFrame(
          loader.values(column.dtype, self.trading_days, self.sids)[
              slice_
          ],
          index=self.trading_days[slice_],
          columns=self.assets,
      )
  
imports: import operator
  from unittest import skipIf
  from nose_parameterized import parameterized
  from pandas import Timestamp, DataFrame
  from pandas.util.testing import assert_frame_equal
  from zipline.lib.labelarray import LabelArray
  from zipline.pipeline import Pipeline
  from zipline.pipeline.data import USEquityPricing
  from zipline.pipeline.data.dataset import Column
  from zipline.pipeline.data.testing import TestingDataSet
  from zipline.pipeline.domain import US_EQUITIES
  from zipline.testing.fixtures import WithSeededRandomPipelineEngine, WithTradingSessions, ZiplineTestCase
  from zipline.utils.numpy_utils import datetime64ns_dtype
  from zipline.utils.pandas_utils import ignore_pandas_nan_categorical_warning, new_pandas, skip_pipeline_new_pandas
label_desc: Use image node_id 2 for calling the LatestTestCase obj's underlying member method code with example usage: obj.expected_latest(column, slice_) and returns: DataFrame, LabelArray