diff --git a/labs06/task02.py b/labs06/task02.py
index 204e4c6..dd862c2 100755
--- a/labs06/task02.py
+++ b/labs06/task02.py
@@ -6,9 +6,7 @@ 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
@@ -60,29 +58,11 @@ def add_borough(dane):
 
 def write_plot(dane, filename):
     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()
-
+    Hist_out = hist_data.plot(kind='bar', alpha=0.5, title="Appartments in Distrinct",fontsize=5, figsize=(7, 5))
+    fig = Hist_out.get_figure()
     fig.savefig(filename)
 
-
 def mean_price(dane, room_number):
     AVGdane = dane[dane.Rooms == room_number]
     AVGdane = round(AVGdane.Expected.mean(),2)
@@ -90,10 +70,17 @@ def mean_price(dane, room_number):
 
 
 def find_13(dane):
-    pass
+    add_borough(dane)
+    List_13 = []
+    WhatLookFor = dane['Borough'].loc[dane['Floor'] == 13]
+    for j in WhatLookFor:
+        List_13.append(j)
+    return List_13
 
 def find_best_flats(dane):
-    pass
+    add_borough(dane)
+    TheBest = dane[(dane.Borough == 'Winogrady') & (dane.Rooms == 3) & (dane.Floor == 1)]
+    return TheBest
 
 def main():
     dane = wczytaj_dane()
@@ -110,7 +97,7 @@ def main():
           .format(mean_price(dane, 3)))
 
     roomCheapest = cheapest_flats(dane, 5)
-    #print roomCheapest
+    print roomCheapest
 
     district = add_borough(dane['Location'])
     dane['Borough'] = district.values
@@ -118,5 +105,12 @@ def main():
 
     write_plot(dane, 'plot.png')
 
+    list_13 = find_13(dane)
+    print list_13
+
+    TheBestFlat = find_best_flats(dane)
+    print TheBestFlat['Location']
+
+
 if __name__ == "__main__":
     main()