How to use the pdpipe.basic_stages.ColDrop function in pdpipe

def test_coldrop_one_col():
    """Testing the ColDrop pipeline stage."""
    df = _test_df()
    assert 'num1' in df.columns
    stage = ColDrop('num1')
    res_df = stage.apply(df)
    assert 'num1' not in res_df.columns
    assert 'num2' in res_df.columns
    assert 'char' in res_df.columns

def test_coldrop_1(self):
        """Testing the ColDrop pipline stage."""
        df = pd.DataFrame(
            data=[[1, 'a'], [2, 'b']],
            index=[1, 2],
            columns=['num', 'char']
        )
        self.assertEqual(
            collections.Counter(df.columns),
            collections.Counter(['num', 'char']))
        self.assertTrue('num' in df.columns)
        stage = ColDrop('num')
        df = stage.apply(df)
        self.assertTrue('num' not in df.columns)
        self.assertTrue('char' in df.columns)

def test_coldrop_non_str_lbl():
    """Testing the ColDrop pipeline stage."""
    df = _test_df2()
    assert 2 in df.columns
    stage = ColDrop(2)
    res_df = stage.apply(df)
    assert 2 not in res_df.columns
    assert 'num1' in res_df.columns
    assert False in res_df.columns

def test_coldrop_missing_col():
    """Testing the ColDrop pipeline stage."""
    df = _test_df()
    assert 'num1' in df.columns
    stage = ColDrop('num3')
    with pytest.raises(FailedPreconditionError):
        res_df = stage.apply(df)
    stage = ColDrop('num3', errors='ignore')
    res_df = stage.apply(df)
    assert res_df.equals(df)

def test_coldrop_missing_col():
    """Testing the ColDrop pipeline stage."""
    df = _test_df()
    assert 'num1' in df.columns
    stage = ColDrop('num3')
    with pytest.raises(FailedPreconditionError):
        res_df = stage.apply(df)
    stage = ColDrop('num3', errors='ignore')
    res_df = stage.apply(df)
    assert res_df.equals(df)

def test_coldrop_multi_col():
    """Testing the ColDrop pipeline stage."""
    df = _test_df()
    assert 'num1' in df.columns
    assert 'num2' in df.columns
    stage = ColDrop(['num1', 'num2'])
    res_df = stage.apply(df)
    assert 'num1' not in res_df.columns
    assert 'num2' not in res_df.columns
    assert 'char' in res_df.columns

def test_attribute_stage():
    """Testing attribute pipeline stages."""
    pipeline = pdp.ColDrop('name').Bin({'speed': [5]}, drop=True)
    assert isinstance(pipeline, PdPipeline)
    assert isinstance(pipeline[0], ColDrop)
    assert isinstance(pipeline[1], Bin)
    df = _some_df()
    res_df = pipeline(df)
    assert 'speed' in res_df.columns
    assert 'name' not in res_df.columns

def test_coldrop_lambda():
    """Testing the ColDrop pipeline stage."""
    df = _test_df()
    assert 'num1' in df.columns
    assert 'num2' in df.columns
    stage = ColDrop(lambda col: 'num' in col.name)
    res_df = stage.apply(df)
    assert 'num1' not in res_df.columns
    assert 'num2' not in res_df.columns
    assert 'char' in res_df.columns

def __init__(self, columns, errors=None, **kwargs):
        self._columns = columns
        self._errors = errors
        self._columns_str = _list_str(self._columns)
        if not callable(columns):
            self._columns = _interpret_columns_param(columns)
        super_kwargs = {
            'exmsg': ColDrop._DEF_COLDROP_EXC_MSG.format(self._columns_str),
            'appmsg': ColDrop._DEF_COLDROP_APPLY_MSG.format(self._columns_str),
            'desc': self._default_desc()
        }
        super_kwargs.update(**kwargs)
        super().__init__(**super_kwargs)

def __init__(self, columns, errors=None, **kwargs):
        self._columns = columns
        self._errors = errors
        self._columns_str = _list_str(self._columns)
        if not callable(columns):
            self._columns = _interpret_columns_param(columns)
        super_kwargs = {
            'exmsg': ColDrop._DEF_COLDROP_EXC_MSG.format(self._columns_str),
            'appmsg': ColDrop._DEF_COLDROP_APPLY_MSG.format(self._columns_str),
            'desc': self._default_desc()
        }
        super_kwargs.update(**kwargs)
        super().__init__(**super_kwargs)