How to use the pdpipe.ColDrop function in pdpipe

def test_encode_in_pipelin_fit_n_transform():
    drop_name = pdp.ColDrop('name')
    encode_stage = Encode()
    pline = drop_name + encode_stage

    df = _some_df()

    with pytest.raises(UnfittedPipelineStageError):
        res_df = pline.transform(df)

    res_df = pline.fit(df)
    assert 'lbl' in res_df.columns
    assert 'name' in res_df.columns
    assert res_df['lbl'][1] == 'acd'
    assert res_df['lbl'][2] == 'alk'
    assert res_df['lbl'][3] == 'alk'

    res_df = pline.transform(df)

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_encode_in_pipeline():
    drop_name = pdp.ColDrop('name')
    encode_stage = Encode()
    pline = drop_name + encode_stage

    df = _some_df()
    res_df = pline(df)
    assert 'lbl' in res_df.columns
    assert 'name' not in res_df.columns
    assert res_df['lbl'][1] == 0
    assert res_df['lbl'][2] == 1
    assert res_df['lbl'][3] == 1

    # check fitted pipeline
    df2 = _some_df2()
    res_df2 = pline(df2)
    assert 'lbl' in res_df2.columns
    assert res_df2['lbl'][1] == 1