commit

labs06/task02.py

@@ -10,10 +10,12 @@ def wczytaj_dane():
     return pd.DataFrame(mieszkania)
 
 def most_common_room_number (dane):
-    return dane['Rooms'].value_counts().head()
+    most_common =  dane['Rooms'].value_counts().head()
+    return most_common
 
 def cheapest_flats(dane, n):
-    return dane.sort_values('Expected').head(n)
+    cheapest = dane.sort_values('Expected').head(n)
+    return cheapest
 
 def find_borough(desc):
     dzielnice = ['Stare Miasto',
@@ -41,13 +43,16 @@ def write_plot(dane, filename):
     figure_data.savefig ( filename )
 
 def mean_price(dane, room_number):
-    pass
+    rooms = dane[ dane['Rooms']==room_number]['Expected'].mean()
+    return rooms
 
 def find_13(dane):
-    pass
+    floor_13 = dane[dane['Floor'] == 13]['Borough'].values
+    return floor_13
 
 def find_best_flats(dane):
-    pass
+    best_flats = dane[(dane['Borough'] == 'Winogrady') & (dane['Rooms'] == 3) & (dane['Floor'] == 1)]
+    return best_flats
 
 def main ( ):
     dane = wczytaj_dane ( )
@@ -55,10 +60,16 @@ def main():
 
     print("Najpopularniejsza liczba pokoi w mieszkaniu to: {}".format ( most_common_room_number ( dane ) ))
 
-    print("Najtańsze mieszkania, to: {}".format(cheapest_flats(dane, 5)))
-
     print("{} to najłądniejsza dzielnica w Poznaniu.".format ( find_borough ( "Grunwald i Jeżyce" ) ))
 
+    print("Średnia cena mieszkania 3-pokojowego, to: {:.2f}".format ( mean_price ( dane , 3 ) ))
+
+    dane = add_borough(dane)
+
+    print("Dzielnice z ofertami na 13 pietrze: {}".format ( find_13 ( dane ) ))
+
+    print("Najlepsze oferty: {}".format ( find_best_flats ( dane ) ))
+
 
 if __name__ == "__main__":
     main ( )