code: def test_atleast_2d_column_default():
      import warnings
  
      assert np.all(
          atleast_2d_column_default([1, 2, 3]) == [[1], [2], [3]]
      )
  
      assert atleast_2d_column_default(1).shape == (1, 1)
      assert atleast_2d_column_default([1]).shape == (1, 1)
      assert atleast_2d_column_default([[1]]).shape == (1, 1)
      assert atleast_2d_column_default([[[1]]]).shape == (1, 1, 1)
  
      assert atleast_2d_column_default([1, 2, 3]).shape == (3, 1)
      assert atleast_2d_column_default([[1], [2], [3]]).shape == (3, 1)
  
      with warnings.catch_warnings() as w:
          warnings.filterwarnings(
              "ignore", "the matrix subclass", PendingDeprecationWarning
          )
          assert (
              type(atleast_2d_column_default(np.matrix(1)))
              == np.ndarray
          )
          assert w is None
  
      global have_pandas
      if have_pandas:
          assert (
              type(atleast_2d_column_default(pandas.Series([1, 2])))
              == np.ndarray
          )
          assert (
              type(
                  atleast_2d_column_default(
                      pandas.DataFrame([[1], [2]])
                  )
              )
              == np.ndarray
          )
          assert (
              type(
                  atleast_2d_column_default(
                      pandas.Series([1, 2]), preserve_pandas=True
                  )
              )
              == pandas.DataFrame
          )
          assert (
              type(
                  atleast_2d_column_default(
                      pandas.DataFrame([[1], [2]]), preserve_pandas=True
                  )
              )
              == pandas.DataFrame
          )
          s = pandas.Series(
              [10, 11, 12], name="hi", index=["a", "b", "c"]
          )
          df = atleast_2d_column_default(s, preserve_pandas=True)
          assert isinstance(df, pandas.DataFrame)
          assert np.all(df.columns == ["hi"])
          assert np.all(df.index == ["a", "b", "c"])
      with warnings.catch_warnings() as w:
          warnings.filterwarnings(
              "ignore", "the matrix subclass", PendingDeprecationWarning
          )
          assert (
              type(
                  atleast_2d_column_default(
                      np.matrix(1), preserve_pandas=True
                  )
              )
              == np.ndarray
          )
          assert w is None
      assert (
          type(
              atleast_2d_column_default([1, 2, 3], preserve_pandas=True)
          )
          == np.ndarray
      )
  
      if have_pandas:
          had_pandas = have_pandas
          try:
              have_pandas = False
              assert (
                  type(
                      atleast_2d_column_default(
                          pandas.Series([1, 2]), preserve_pandas=True
                      )
                  )
                  == np.ndarray
              )
              assert (
                  type(
                      atleast_2d_column_default(
                          pandas.DataFrame([[1], [2]]),
                          preserve_pandas=True,
                      )
                  )
                  == np.ndarray
              )
          finally:
              have_pandas = had_pandas
  
imports: import sys
  import numpy
  import six
  from six.moves import cStringIO
  from .compat import optional_dep_ok
label_desc: Use image node_id 4 for calling a global function with example usage: test_atleast_2d_column_default() without return types