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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def create_multiple_expectations(df, columns, expectation_type, *args, **kwargs):
 """Creates an identical expectation for each of the given columns with the specified arguments, if any. Args: df (great_expectations.dataset):
 A great expectations dataset object. columns (list):
 A list of column names represented as strings. expectation_type (string):
 The expectation type. Raises: KeyError if the provided column does not exist. AttributeError if the provided expectation type does not exist or df is not a valid great expectations dataset. Returns: A list of expectation results. """

    expectation = getattr(df, expectation_type)
    results = list()

    for column in columns:
        results.append(expectation(column, *args,  **kwargs))

    return results