def binary(dataframe, entity_id, feature_id):
    """
    Create binary feature dataframe using provided dataset, entity, and feature.

    :param dataframe: Input dataframe to create binary features
    :type dataframe: cudf.DataFrame
    :param entity_id: Entity ID. Must be a column within `dataframe`
    :type entity_id: str
    :param feature_id: Feature ID. Must be a column within `dataframe`
    :type feature_id: str
    :return: dataframe
    :rtype: cudf.DataFrame

    Examples
    --------
    >>> import cudf
    >>> import clx.features
    >>> df = cudf.DataFrame(
            {
                "time": [1, 2, 3],
                "user": ["u1", "u2", "u1",],
                "computer": ["c1", "c1", "c3"],
            }
        )
    >>> output = clx.features.binary(df, "user", "computer")
    >>> output
            c1	c3
        user
        u1	1.0	1.0
        u2	1.0	0.0
    """
    if entity_id and feature_id not in dataframe.columns:
        raise Exception(
            "{0} and {1} must be column names in the input dataframe".format(
                entity_id, feature_id
            )
        )
    df_grouped = dataframe.groupby([entity_id, feature_id]).count().reset_index()
    df_output = df_grouped.pivot(index=entity_id, columns=feature_id).fillna(0)
    df_output[df_output != 0] = 1
    return df_output