forked from tdwojak/Python2017
86 lines
2.0 KiB
Python
Executable File
86 lines
2.0 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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import pandas as pd
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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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dane = pd.read_csv('mieszkania.csv',
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sep=',',
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encoding='utf-8')
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return dane
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def most_common_room_number(dane):
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return dane.Rooms.mode()[0]
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def cheapest_flats(dane, n):
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dane = dane.sort_values('Expected',ascending=True)
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return dane.head(n)
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def find_borough(desc):
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dzielnice = ['Stare Miasto',
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'Wilda',
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'Jeżyce',
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'Rataje',
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'Piątkowo',
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'Winogrady',
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'Miłostowo',
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'Dębiec']
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for dzielnica in dzielnice:
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if desc.find(dzielnica)>=0:
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return dzielnica
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return 'Inne'
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def add_borough(dane):
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borough = []
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for current_location in dane:
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borough.append(find_borough(current_location))
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return pd.Series(borough)
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def write_plot(dane, filename):
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dane['Borough'].hist()
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plt.savefig(filename)
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def mean_price(dane, room_number):
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dane = dane[dane.Rooms == room_number]
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return round(dane.Expected.mean(),2)
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def find_13(dane):
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dane = dane[dane.Floor == 13]
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return list(dane.Borough)
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def find_best_flats(dane):
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dane = dane[(dane.Borough=='Winogrady') & (dane.Rooms==3) & (dane.Floor == 1)]
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return dane
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def main():
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dane = wczytaj_dane()
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print(dane[:5])
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print("Najpopularniejsza liczba pokoi w mieszkaniu to: {}"
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.format(most_common_room_number(dane)))
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najtansze = cheapest_flats(dane,10)
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print("{} to najłądniejsza dzielnica w Poznaniu."
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.format(find_borough("Grunwald i Jeżyce")))
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dzielnice = add_borough(dane['Location'])
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dane['Borough'] = dzielnice.values
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write_plot(dane,'wykres.png')
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print("Średnia cena mieszkania 3-pokojowego, to: {}"
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.format(mean_price(dane, 3)))
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find_13(dane)
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find_best_flats(dane)
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if __name__ == "__main__":
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main()
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