task02 ok

labs06/task02.py

@@ -1,14 +1,24 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
+import pandas as pd
+import matplotlib.pyplot as plt
+
 
 def wczytaj_dane():
-    pass
+    csv_data = pd.read_csv('mieszkania.csv', index_col='Id')
+    return pd.DataFrame(csv_data)
+
 
 def most_common_room_number(dane):
-    pass
+
+    dane_agg = dane["Rooms"].value_counts()
+    return dane_agg.index.tolist()[0]
+
 
 def cheapest_flats(dane, n):
-    pass
+    dane_cheapest = dane.sort_values(by=["Expected"])[:n]
+    return dane_cheapest
+
 
 def find_borough(desc):
     dzielnice = ['Stare Miasto',
@@ -19,36 +29,72 @@ def find_borough(desc):
                  'Winogrady',
                  'Miłostowo',
                  'Dębiec']
-    pass
+    first = ""
+    found = False
+    for dz in dzielnice:
+        if dz in desc:
+            first = dz
+            found = True
+            break
+
+    if not found:
+        return 'Inne'
+    else:
+        return first
 
 
 def add_borough(dane):
-    pass
+    dane['Borough'] = dane['Location'].map(lambda loc: find_borough(loc))
+
 
 def write_plot(dane, filename):
-    pass
+
+    dane['Borough'].value_counts().plot(kind='bar', figsize = (10, 10))
+    plt.savefig(filename)
+
 
 def mean_price(dane, room_number):
-    pass
+    ff = dane[dane['Rooms'] == room_number]
+    return ff['Expected'].mean()
+
 
 def find_13(dane):
-    pass
+
+    ff = dane[dane['Floor'] == 13]
+    return ff['Borough'].unique()
+
 
 def find_best_flats(dane):
-    pass
+
+    bf = dane[(dane['Rooms'] == 3) & (dane['Floor'] == 1) & (dane['Borough'] == 'Winogrady')]
+    return bf
+
 
 def main():
+
     dane = wczytaj_dane()
+    add_borough(dane)
     print(dane[:5])
 
+
     print("Najpopularniejsza liczba pokoi w mieszkaniu to: {}"
           .format(most_common_room_number(dane)))
 
     print("{} to najłądniejsza dzielnica w Poznaniu."
-          .format(find_borough("Grunwald i Jeżyce"))))
+          .format(find_borough("Grunwald i Jeżyce")))
 
     print("Średnia cena mieszkania 3-pokojowego, to: {}"
          .format(mean_price(dane, 3)))
 
+    print("Dzielnice z mieszkaniami na 13 piętrze, to: {}"
+          .format(find_13(dane)))
+
+    ile = 10
+    print("Najtańsze oferty mieszkań, to: {}"
+          .format(cheapest_flats(dane, ile)))
+
+    write_plot(dane, 'mieszkania_plot.png')
+
+
 if __name__ == "__main__":
     main()