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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 conditional_distribution(self, values, inplace=True):
 """ Returns Conditional Probability Distribution after setting values to 1. Parameters values: list or array_like A list of tuples of the form (variable_name, variable_state). The values on which to condition the Joint Probability Distribution. inplace: Boolean (default True) If False returns a new instance of JointProbabilityDistribution Examples -------- x2 x3 P(x2,x3) x2_0 x3_0 0.2500 x2_0 x3_1 0.2500 x2_1 x3_0 0.2500 x2_1 x3_1 0.2500 """

        JPD = self if inplace else self.copy()
        JPD.reduce(values)
        JPD.normalize()
        if not inplace:
            return JPD