gistfile1.txt

#Fitting linear regression model

def linear_regression(neighborhoods):

   neighborhoods_regression = []

   for neighborhood in april.Neighborhood.unique():

       temp = april[april.Neighborhood == neighborhood]

       if len(temp) > 500:

           #Creating test set

           test = temp['Taxi_Order'] + temp['Uber_Order']



           #Deleting unnecessary columns

           del temp['Taxi_Order']

           del temp['Uber_Order']

           del temp['Min']

           del temp['Max']

           del temp['Neighborhood']

           del temp['Date']

           del temp['Uber_Share']

           del temp['Unnamed: 0']

ols.train(temp, test)

           neighborhoods_regression[neighborhood] = float(ols.predict(get_current_conditions()))

   return neighborhoods_regression