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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 _chi_squared(self, proportions, margin, observed):
 """return ndarray of chi-squared measures for proportions' columns. *proportions* (ndarray):
 The basis of chi-squared calcualations *margin* (ndarray):
 Column margin for proportions (See `def _margin`) *observed* (ndarray):
 Row margin proportions (See `def _observed`) """

        n = self._element_count
        chi_squared = np.zeros([n, n])
        for i in xrange(1, n):
            for j in xrange(0, n - 1):
                denominator = 1 / margin[i] + 1 / margin[j]
                chi_squared[i, j] = chi_squared[j, i] = (
                    np.sum(np.square(proportions[:, i] - proportions[:, j]) / observed)
                    / denominator
                )
        return chi_squared