forked from tdwojak/Python2018
109 lines
2.6 KiB
Python
Executable File
109 lines
2.6 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.pyplot as plt
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def wczytaj_dane():
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dane = pd.read_csv("mieszkania.csv")
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print(dane.head())
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return(dane)
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def most_common_room_number(dane):
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return(dane['Rooms'].value_counts().idxmax())
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def cheapest_flats(dane, n):
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p = dane.sort_values(['Expected'], ascending=[0])
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p.head(7)
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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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'Grunwald',
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'Nowe Miasto']
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check = 0
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for dzielnica in dzielnice:
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if dzielnica in desc:
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check = 1
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save_dzielnica = dzielnica
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if check == 1:
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return(save_dzielnica)
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else:
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return("Inne")
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def add_borough(dane):
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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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'Grunwald',
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'Nowe Miasto']
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Borough = []
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column = dane['Location']
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for item in column:
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check = 0
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for dzielnica in dzielnice:
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if dzielnica in item:
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check = 1
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save_dzielnica = dzielnica
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if check == 1:
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Borough.append(save_dzielnica)
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else:
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Borough.append("Inne")
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Borough = pd.DataFrame(Borough)
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dane = pd.concat([dane.reset_index(drop=True), Borough], axis=1)
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print(dane)
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def write_plot(dane, filename):
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dane.groupby('Borough')['Id'].nunique().plot(kind='bar')
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plt.show()
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plt.savefig('output.png')
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def mean_price(dane, room_number):
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p1 = dane[dane['Rooms'] == room_number]
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p2 = p1['Expected']
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return(p2.mean())
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def find_13(dane):
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p1 = dane[dane['Floor'] == 13]
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p1.Location.unique()
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def find_best_flats(dane):
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p_index = dane['Location'].str.contains('Winogrady')
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p = dane[p_index]
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best_flats = p[(p['Rooms'] == 3) & (p['Floor'] == 1)]
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print(best_flats)
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def main():
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dane = wczytaj_dane()
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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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print("{} to najładniejsza dzielnica w Poznaniu."
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.format(find_borough("Grunwald i Jeżyce")))
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print("Średnia cena mieszkania 3-pokojowego, to: {}"
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.format(mean_price(dane, 3)))
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if __name__ == "__main__":
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main()
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