commited tasks

labs06/task02.py

@@ -1,7 +1,14 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
+
+import sys
+reload(sys)
+sys.setdefaultencoding("utf-8")
+
 import pandas as pd
 import numpy as np
+import matplotlib
+import matplotlib.pyplot as plt
 
 def wczytaj_dane():
     rooms_data = pd.read_csv('mieszkania.csv',  # ścieżka  do pliku
@@ -44,10 +51,37 @@ def find_borough(desc):
 
 
 def add_borough(dane):
-    pass
+    boroughArr = []
+    for current_location in dane:
+        findborough =  find_borough(current_location)
+        #print current_location , findborough
+        boroughArr.append(findborough)
+    return pd.Series(boroughArr)
 
 def write_plot(dane, filename):
-    pass
+    add_borough(dane)
+
+    hist_data = dane['Borough'].value_counts()
+
+    # plt.figure()
+
+
+
+    wyplot = hist_data.plot(kind='bar', alpha=0.5, title="Liczba ogloszen mieszkan z podzialem na dzielnice",
+                            fontsize=5, figsize=(7, 5))
+
+    wyplot.set_xlabel("Dzielnice")
+
+    wyplot.set_ylabel("Liczba ogloszen")
+
+    # plt.show()
+
+
+
+    fig = wyplot.get_figure()
+
+    fig.savefig(filename)
+
 
 def mean_price(dane, room_number):
     AVGdane = dane[dane.Rooms == room_number]
@@ -78,7 +112,11 @@ def main():
     roomCheapest = cheapest_flats(dane, 5)
     #print roomCheapest
 
-    
+    district = add_borough(dane['Location'])
+    dane['Borough'] = district.values
+    #print(dane[:5])
+
+    write_plot(dane, 'plot.png')
 
 if __name__ == "__main__":
     main()