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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 balanced_binning_reference(y, ax=None, target='Frequency', bins=4, **kwargs):
 """ BalancedBinningReference generates a histogram with vertical lines showing the recommended value point to bin your data so they can be evenly distributed in each bin. Parameters y : an array of one dimension or a pandas Series ax : matplotlib Axes, default: None This is inherited from FeatureVisualizer and is defined within ``BalancedBinningReference``. target : string, default: "Frequency" The name of the ``y`` variable bins : number of bins to generate the histogram, default: 4 kwargs : dict Keyword arguments that are passed to the base class and may influence the visualization as defined in other Visualizers. """


    # Initialize the visualizer
    visualizer = BalancedBinningReference(ax=ax, bins=bins, target=target, **kwargs)
    
    # Fit and poof the visualizer
    visualizer.fit(y)
    visualizer.poof()