From 3624beaac4af1e8fd24411341ed8ecabbf5c1d49 Mon Sep 17 00:00:00 2001 From: Magdalena Lewandowicz Date: Sat, 23 Jun 2018 17:06:27 +0200 Subject: [PATCH] zadanie --- labs06/task02.py | 35 +++++++++++++++++++++++------------ 1 file changed, 23 insertions(+), 12 deletions(-) mode change 100755 => 100644 labs06/task02.py diff --git a/labs06/task02.py b/labs06/task02.py old mode 100755 new mode 100644 index 9d96016..4e3d11b --- a/labs06/task02.py +++ b/labs06/task02.py @@ -1,15 +1,19 @@ #!/usr/bin/env python # -*- coding: utf-8 -*- +import pandas as pd +import matplotlib.pyplot as plt + def wczytaj_dane(): - pass + dane = pd.read_csv("./mieszkania.csv") + return dane def most_common_room_number(dane): - pass + return dane.Rooms.value_counts().idxmax() def cheapest_flats(dane, n): - pass - + return dane.sort('Expected').head(n) + def find_borough(desc): dzielnice = ['Stare Miasto', 'Wilda', @@ -19,23 +23,30 @@ def find_borough(desc): 'Winogrady', 'Miłostowo', 'Dębiec'] - pass - + for dzielnica in dzielnice: + list = desc.split(' ') + for element in list: + if len(element) > 2 and element == dzielnica: + return dzielnica + break + return "Inne" def add_borough(dane): - pass + dane['Borough'] = dane['Location'].apply(find_borough) + return dane def write_plot(dane, filename): - pass + dane['Borough'].value_counts().plot.bar().get_figure().savefig(filename) def mean_price(dane, room_number): - pass + mean_price = dane.Expected[(dane['Rooms'] == room_number)] + return mean_price.mean() def find_13(dane): - pass + return dane.Location[(dane['Floor'] == 13)].unique() def find_best_flats(dane): - pass + return dane[(dane['Location'] == 'Winogrady') & (dane['Rooms'] == 3) & (dane['Floor'] == 1)] def main(): dane = wczytaj_dane() @@ -45,7 +56,7 @@ def main(): .format(most_common_room_number(dane))) print("{} to najłądniejsza dzielnica w Poznaniu." - .format(find_borough("Grunwald i Jeżyce")))) + .format(find_borough("Grunwald i Jeżyce"))) print("Średnia cena mieszkania 3-pokojowego, to: {}" .format(mean_price(dane, 3)))