import sample as py from davinci.python import val from sklearn.linear_model import LinearRegression def regress(data, factors, y, intercept=True): ols = LinearRegression(fit_intercept=intercept) X=[] Y=[] for item in data: yrec = [item[y]] Y.append(yrec) record = [] X.append(record) for factor in factors: record.append(item[factor]) pass ols.fit(X, Y) intercept = ols.intercept_ coefficients = ols.coef_ return ols purchases = py.sample() ols = regress(purchases, ['age', 'income'], 'spend') coef = ols.coef_.tolist() intercept = ols.intercept_.tolist() pass