pricefix

app.py

@@ -35,6 +35,17 @@ featureToMinMax = {
         'soldDate': (2010, 2025)
     } # Extracted from the data
 
+featureToName = {
+    'number' : 'Street number',
+     'sqm' : 'Size of the apartment in square meters',
+    'rooms' : 'Number of rooms',
+     'monthlyFee' : 'Monthly fee',
+    'monthlyCost' : 'Monthly operating cost',
+    'floor' : 'Floor',
+    'yearBuilt' : 'Year built',
+     'streetName' : 'Name of street',
+}
+
 def downloadAutogluonModel():
     # Download saved Autogluon model from Hopsworks
     project = hopsworks.login(
@@ -121,14 +132,6 @@ def fixChange(df):
     
     return df
 
-def fixChange(df):
-    # Set change to be the difference between the current and previous price
-    df['change'] = df['value'].diff()
-    # If the change is Nan set it to 0
-    df['change'] = df['change'].fillna(0)
-    
-    return df
-
 def cleanAddress(x):
     # Remove "-" from the street
     x = ''.join(x.split('-'))
@@ -211,13 +214,12 @@ def parsePrice(price):
 
 def addDotsToPrice(price):
     # Takes an int like 1000000 and returns a string like 1.000.000
-    price = str(price)
+    price = str(price)[::-1]
     toReturn = ''
     
-    # Make a reverse loop
-    for i in range(len(price) - 1, -1, -1):
-        toReturn += price[i]
-        if i % 3 == 0 and i != 0:
+    for i, c in enumerate(price):
+        toReturn += c
+        if (len(price) - i) % 3 == 1 and i != len(price) - 1:
             toReturn += '.'
     
     # Reverse the string
@@ -273,9 +275,9 @@ def isValidInput(streetName, number, sqm, rooms, monthlyFee, monthlyCost, floor,
         MIN = featureToMinMax[name][0]
         MAX = featureToMinMax[name][1]
         if val < MIN:
-            return f'{name} is too low'
+            return f'{featureToName.get(name)} is too low'
         if val > MAX:
-            return f'{name} is too high'
+            return f'{featureToName.get(name)} is too high'
     
     return None
 
@@ -304,18 +306,15 @@ def sthlm(streetName, number, sqm, rooms, monthlyFee, monthlyCost, floor, yearBu
     if inputErrors is not None:
         return '', inputErrors
     lat, lon = getAddressInfo(streetName, number)
-    print('1')
     # If none
     if lat is None or lon is None:
         return '', 'Address not found in the OpenStreetMap dataset (Nominatim), please try another address'
-    print('2')
 
     agency = 'Notar' # Make fun if categorical works
     brf = 'BRF Kartboken 1' # TODO: remove
     dates = getDates()
     input_variables = pd.DataFrame(
             columns=columnHeaders)
-    print('3')
     
     for soldDate in dates.keys():
         # gdp, unemployment, interestRate = getFinancialInfo(soldDate)
@@ -325,12 +324,9 @@ def sthlm(streetName, number, sqm, rooms, monthlyFee, monthlyCost, floor, yearBu
         input_variables = input_variables.append(
             pd.DataFrame(
                 [[streetName,number,sqm,rooms,soldDate,monthlyFee,monthlyCost,floor,yearBuilt,brf,agency,lat,lon]], columns=columnHeaders))
-    print('4')
     
     df = populateApartmentData(input_variables)  
-    print('5')
     df = normalizeData(df)
-    print('6')
     df = xgbFix(df)
 
     pricePred = None
@@ -338,9 +334,7 @@ def sthlm(streetName, number, sqm, rooms, monthlyFee, monthlyCost, floor, yearBu
         # pricePred = autoPred(df)
         '', 'Autogluon is not working right now, please try again later'
     else:
-        print('7')
         pricePred = xgboostPred(df)
-        print('8')
 
     explanations = list(dates.values())
     result = []
@@ -365,16 +359,7 @@ def sthlm(streetName, number, sqm, rooms, monthlyFee, monthlyCost, floor, yearBu
 numericalInputs = ['number', 'sqm','rooms', 'monthlyFee','monthlyCost','floor','yearBuilt']
 inputs = [gr.inputs.Textbox(lines=1, label='streetName')]
 
-featureToName = {
-    'number' : 'Street number',
-     'sqm' : 'Size of the apartment in square meters',
-    'rooms' : 'Number of rooms',
-     'monthlyFee' : 'Monthly fee',
-    'monthlyCost' : 'Monthly operating cost',
-    'floor' : 'Floor',
-    'yearBuilt' : 'Year built',
-     'streetName' : 'Name of street',
-}
+
     
 # Generate the input form
 for feature in numericalInputs: