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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 validate_sample_frame(sample_frame):
 """Makes sure that `sample_frame` has the columns we expect. :param DataFrame sample_frame: A sample data frame. :return: True (or raises an exception) :raises TypeError: if sample_frame is not a pandas DataFrame :raises ValueError: if columns are missing or the wrong type """

    if not isinstance(sample_frame, pd.core.frame.DataFrame):
        raise TypeError("Expected a pandas DataFrame, received {}".format(type(sample_frame)))
    for col in ['Sample', 'Target', 'Cq']:
        if col not in sample_frame:
            raise ValueError("Missing column {} in sample frame".format(col))
    if sample_frame['Cq'].dtype.kind != 'f':
        raise ValueError("Expected Cq column to have float type; has type {} instead".format(str(sample_frame['Cq'].dtype)))
    return True