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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 pass_for_numeric_dtypes_or_raise_array(x):
 """ Use the utility `to_numeric` to check that x is convertible to numeric values, and then convert. Any errors are reported back to the user. Parameters x: list, array, Series, DataFrame Notes ------ This actually allows objects like timedeltas (converted to microseconds), and strings as numbers. """

    try:
        if isinstance(x, (pd.Series, pd.DataFrame)):
            v = pd.to_numeric(x.squeeze())
        else:
            v = pd.to_numeric(np.asarray(x).squeeze())

        if v.size == 0:
            raise ValueError("Empty array/Series passed in.")
        return v

    except:
        raise ValueError("Values must be numeric: no strings, datetimes, objects, etc.")