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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 fit(self, y, **kwargs):
 """ Sets up y for the histogram and checks to ensure that ``y`` is of the correct data type. Fit calls draw. Parameters y : an array of one dimension or a pandas Series kwargs : dict keyword arguments passed to scikit-learn API. """


        #throw an error if y has more than 1 column
        if y.ndim > 1:
            raise YellowbrickValueError("y needs to be an array or Series with one dimension") 

        # Handle the target name if it is None.
        if self.target is None:
            self.target = 'Frequency'

        self.draw(y)
        return self