forked from tdwojak/Python2017
commited tasks
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@ -6,9 +6,7 @@ reload(sys)
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sys.setdefaultencoding("utf-8")
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sys.setdefaultencoding("utf-8")
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import pandas as pd
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import pandas as pd
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import numpy as np
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import matplotlib
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import matplotlib.pyplot as plt
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def wczytaj_dane():
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def wczytaj_dane():
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rooms_data = pd.read_csv('mieszkania.csv', # ścieżka do pliku
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rooms_data = pd.read_csv('mieszkania.csv', # ścieżka do pliku
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@ -60,29 +58,11 @@ def add_borough(dane):
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def write_plot(dane, filename):
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def write_plot(dane, filename):
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add_borough(dane)
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add_borough(dane)
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hist_data = dane['Borough'].value_counts()
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hist_data = dane['Borough'].value_counts()
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Hist_out = hist_data.plot(kind='bar', alpha=0.5, title="Appartments in Distrinct",fontsize=5, figsize=(7, 5))
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# plt.figure()
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fig = Hist_out.get_figure()
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wyplot = hist_data.plot(kind='bar', alpha=0.5, title="Liczba ogloszen mieszkan z podzialem na dzielnice",
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fontsize=5, figsize=(7, 5))
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wyplot.set_xlabel("Dzielnice")
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wyplot.set_ylabel("Liczba ogloszen")
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# plt.show()
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fig = wyplot.get_figure()
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fig.savefig(filename)
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fig.savefig(filename)
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def mean_price(dane, room_number):
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def mean_price(dane, room_number):
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AVGdane = dane[dane.Rooms == room_number]
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AVGdane = dane[dane.Rooms == room_number]
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AVGdane = round(AVGdane.Expected.mean(),2)
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AVGdane = round(AVGdane.Expected.mean(),2)
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@ -90,10 +70,17 @@ def mean_price(dane, room_number):
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def find_13(dane):
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def find_13(dane):
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pass
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add_borough(dane)
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List_13 = []
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WhatLookFor = dane['Borough'].loc[dane['Floor'] == 13]
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for j in WhatLookFor:
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List_13.append(j)
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return List_13
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def find_best_flats(dane):
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def find_best_flats(dane):
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pass
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add_borough(dane)
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TheBest = dane[(dane.Borough == 'Winogrady') & (dane.Rooms == 3) & (dane.Floor == 1)]
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return TheBest
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def main():
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def main():
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dane = wczytaj_dane()
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dane = wczytaj_dane()
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@ -110,7 +97,7 @@ def main():
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.format(mean_price(dane, 3)))
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.format(mean_price(dane, 3)))
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roomCheapest = cheapest_flats(dane, 5)
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roomCheapest = cheapest_flats(dane, 5)
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#print roomCheapest
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print roomCheapest
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district = add_borough(dane['Location'])
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district = add_borough(dane['Location'])
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dane['Borough'] = district.values
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dane['Borough'] = district.values
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@ -118,5 +105,12 @@ def main():
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write_plot(dane, 'plot.png')
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write_plot(dane, 'plot.png')
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list_13 = find_13(dane)
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print list_13
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TheBestFlat = find_best_flats(dane)
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print TheBestFlat['Location']
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if __name__ == "__main__":
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if __name__ == "__main__":
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main()
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main()
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