now we can still measure the quality of fit with multivariate regression using -squared it works the same wayalthough one thing you need to assume when you're doing multivariate regression is that the factors themselves are not dependent on each other and that' not always true so sometimes you need to keep that little caveat in the back of your head for examplein this model we're going to assume that mileage and age of the car are not relatedbut in factthey're probably pretty tightly relatedthis is limitation of this techniqueand it might not be capturing an effect at all multivariate regression using python fortunately there' tubutnpefm package available for python that makes doing multivariate regression pretty easy let' just dive in and see how it works let' do some multivariate regression using python we're going to use some real data here about car values from the kelley blue book jnqpsuqboebtbtqe eg qesfbe@fydfm iuuq deotvoephtpgudpn efnz%bub djfodfdbstymt we're going to introduce new package here called qboebtwhich lets us deal with tabular data really easily it lets us read in tables of data and rearrange themand modify themand slice them and dice them in different ways we're going to be using that lot going forward we're going to import qboebt as qeand qe has sfbe@&ydfm function that we can use to go ahead and read microsoft excel spreadsheet from the web through http sopretty awesome capabilities of pandas there 've gone ahead and hosted that file for you on my own domainand if we run thatit will load it into what' called %bub'sbnf object that we're referring to as eg now can call ifbe on this %bub'sbnf to just show the first few lines of itegifbe