forked from tdwojak/Python2018
56 lines
1.4 KiB
Python
56 lines
1.4 KiB
Python
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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def wczytaj_dane():
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return pd.read_csv('mieszkania.csv')
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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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return dane.sort_values('Expected', axis=0, ascending=True)[: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 dzielnica in desc:
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return dzielnica
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return 'Inne'
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def add_borough(dane):
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dane['Borough'] = dane['Location'].apply(find_borough)
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def write_plot(dane, filename):
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# TODO
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pass
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def mean_price(dane, room_number):
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return dane[dane['Rooms'] == room_number]['Expected'].mean()
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def find_13(dane):
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return dane[dane['Floor'] == 13]['Borough'].unique()
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def find_best_flats(dane):
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return dane[(dane['Borough'] == 'Winogrady') & (dane['Floor'] == 1) & (dane['Rooms'] == 3)]
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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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print("{} to najłądniejsza 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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