Update app.py

app.py

@@ -11,9 +11,9 @@ from tqdm import tqdm
 
 # Login to hopsworks and get the feature store
 
-
-
-columnHeaders = ['area','streetName','number','sqm','rooms','soldDate','monthlyFee','monthlyCost','floor','yearBuilt','agency','lat','lon','gdp','unemployment','interestRate']
+# TODO: Remove brf
+# area;streetName;number;sqm;rooms;soldDate;monthlyFee;monthlyCost;floor;yearBuilt;brf;agency;lat;lon;gdp;unemployment;interestRate
+columnHeaders = ['area','streetName','number','sqm','rooms','soldDate','monthlyFee','monthlyCost','floor','yearBuilt', 'brf','agency','lat','lon','gdp','unemployment','interestRate']
 
 
 def downloadModel():
@@ -91,14 +91,14 @@ def sthlm(streetName, area, number, sqm, rooms, monthlyFee, monthlyCost, floor,
     soldDate = '2021-01-01' # TODO
     price = None
     agency = None
-    brf = None
+    brf = 'BRF Kartboken 1' # TODO: remove
     lat, lon = getAddressInfo(streetName, number)
     gdp, unemployment, interestRate = getFinancialInfo(soldDate)
 
     # Parse the input so we can run it through the model
     # Create a dataframe from the input values
     input_variables = pd.DataFrame(
-        [[area,streetName,number,sqm,rooms,soldDate,monthlyFee,monthlyCost,floor,yearBuilt,agency,lat,lon,gdp,unemployment,interestRate]], columns=columnHeaders)
+        [[area,streetName,number,sqm,rooms,soldDate,monthlyFee,monthlyCost,floor,yearBuilt, brf,agency,lat,lon,gdp,unemployment,interestRate]], columns=columnHeaders)
     
     df = normalizeData(input_variables)