forked from tdwojak/Python2017
100 lines
2.1 KiB
Python
Executable File
100 lines
2.1 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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csv_data = pd.read_csv('mieszkania.csv', index_col='Id')
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return pd.DataFrame(csv_data)
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def most_common_room_number(dane):
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dane_agg = dane["Rooms"].value_counts()
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return dane_agg.index.tolist()[0]
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def cheapest_flats(dane, n):
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dane_cheapest = dane.sort_values(by=["Expected"])[:n]
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return dane_cheapest
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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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first = ""
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found = False
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for dz in dzielnice:
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if dz in desc:
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first = dz
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found = True
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break
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if not found:
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return 'Inne'
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else:
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return first
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def add_borough(dane):
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dane['Borough'] = dane['Location'].map(lambda loc: find_borough(loc))
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def write_plot(dane, filename):
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dane['Borough'].value_counts().plot(kind='bar', figsize = (10, 10))
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plt.savefig(filename)
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def mean_price(dane, room_number):
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ff = dane[dane['Rooms'] == room_number]
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return ff['Expected'].mean()
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def find_13(dane):
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ff = dane[dane['Floor'] == 13]
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return ff['Borough'].unique()
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def find_best_flats(dane):
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bf = dane[(dane['Rooms'] == 3) & (dane['Floor'] == 1) & (dane['Borough'] == 'Winogrady')]
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return bf
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def main():
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dane = wczytaj_dane()
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add_borough(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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print("Dzielnice z mieszkaniami na 13 piętrze, to: {}"
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.format(find_13(dane)))
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ile = 10
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print("Najtańsze oferty mieszkań, to: {}"
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.format(cheapest_flats(dane, ile)))
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write_plot(dane, 'mieszkania_plot.png')
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if __name__ == "__main__":
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main() |