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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 column_correlations(self, X):
 """Returns the column correlations with each principal component."""

        utils.validation.check_is_fitted(self, 's_')

        # Convert numpy array to pandas DataFrame
        if isinstance(X, np.ndarray):
            X = pd.DataFrame(X)

        row_pc = self.row_coordinates(X)

        return pd.DataFrame({
            component: {
                feature: row_pc[component].corr(X[feature])
                for feature in X.columns
            }
            for component in row_pc.columns
        })