Computational Thinking, Python, Linear Algebra, Linear Regression, Jupyter Notebook.
lstsq': 'scipylstq'} pd.options.display.float_format = '{:,.9f}'.format df = pd.DataFrame(index=row_names, columns=['Time', 'Error']) for name in row_names: fcn = name2func[name] t = timeit.timeit(fcn + '(A,b)', number=5, globals=globals()) coeffs = locals()[fcn](A, b) df.set_value(name, 'Time', t)