causalml/metrics/visualize.py [77:89]:
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    assert ((outcome_col in df.columns) and (treatment_col in df.columns) or
            treatment_effect_col in df.columns)

    df = df.copy()
    np.random.seed(random_seed)
    random_cols = []
    for i in range(10):
        random_col = '__random_{}__'.format(i)
        df[random_col] = np.random.rand(df.shape[0])
        random_cols.append(random_col)

    model_names = [x for x in df.columns if x not in [outcome_col, treatment_col,
                                                      treatment_effect_col]]
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causalml/metrics/visualize.py [185:197]:
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    assert ((outcome_col in df.columns) and (treatment_col in df.columns) or
            treatment_effect_col in df.columns)

    df = df.copy()
    np.random.seed(random_seed)
    random_cols = []
    for i in range(10):
        random_col = '__random_{}__'.format(i)
        df[random_col] = np.random.rand(df.shape[0])
        random_cols.append(random_col)

    model_names = [x for x in df.columns if x not in [outcome_col, treatment_col,
                                                      treatment_effect_col]]
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