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wagner.agnieszka 2018-06-22 22:38:06 +02:00
parent 7a8dadbe3b
commit 49fe26305c
1 changed files with 58 additions and 15 deletions
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labs06/task02.py
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@ -1,14 +1,15 @@
#!/usr/bin/env python #!/usr/bin/env python
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import pandas as pd
import matplotlib.pyplot as plt
def wczytaj_dane(): def wczytaj_dane():
import pandas as pd dane = pd.read_csv("mieszkania.csv")
dane = pd.read_csv("labs06/mieszkania.csv") print(dane.head())
dane.head() return(dane)
def most_common_room_number(dane): def most_common_room_number(dane):
dane['Rooms'].value_counts().idxmax() return(dane['Rooms'].value_counts().idxmax())
@ -24,20 +25,61 @@ def find_borough(desc):
'Piątkowo', 'Piątkowo',
'Winogrady', 'Winogrady',
'Miłostowo', 'Miłostowo',
'Dębiec'] 'Dębiec',
pass 'Grunwald',
'Nowe Miasto']
check = 0
for dzielnica in dzielnice:
if dzielnica in desc:
check = 1
save_dzielnica = dzielnica
if check == 1:
return(save_dzielnica)
else:
return("Inne")
def add_borough(dane): def add_borough(dane):
pass dzielnice = ['Stare Miasto',
'Wilda',
'Jeżyce',
'Rataje',
'Piątkowo',
'Winogrady',
'Miłostowo',
'Dębiec',
'Grunwald',
'Nowe Miasto']
Borough = []
column = dane['Location']
for item in column:
check = 0
for dzielnica in dzielnice:
if dzielnica in item:
check = 1
save_dzielnica = dzielnica
if check == 1:
Borough.append(save_dzielnica)
else:
Borough.append("Inne")
Borough = pd.DataFrame(Borough)
dane = pd.concat([dane.reset_index(drop=True), Borough], axis=1)
print(dane)
def write_plot(dane, filename): def write_plot(dane, filename):
pass dane.groupby('Borough')['Id'].nunique().plot(kind='bar')
plt.show()
plt.savefig('output.png')
def mean_price(dane, room_number): def mean_price(dane, room_number):
p1 = dane[dane['Rooms'] == 2] p1 = dane[dane['Rooms'] == room_number]
p2 = p1['Expected'] p2 = p1['Expected']
p2.mean() return(p2.mean())
def find_13(dane): def find_13(dane):
p1 = dane[dane['Floor'] == 13] p1 = dane[dane['Floor'] == 13]
@ -46,17 +88,18 @@ def find_13(dane):
def find_best_flats(dane): def find_best_flats(dane):
p_index = dane['Location'].str.contains('Winogrady') p_index = dane['Location'].str.contains('Winogrady')
p = dane[p_index] p = dane[p_index]
p[(p['Rooms'] == 3) & (p['Floor'] == 1)] best_flats = p[(p['Rooms'] == 3) & (p['Floor'] == 1)]
print(best_flats)
def main(): def main():
dane = wczytaj_dane() dane = wczytaj_dane()
print(dane[:5])
print("Najpopularniejsza liczba pokoi w mieszkaniu to: {}" print("Najpopularniejsza liczba pokoi w mieszkaniu to: {}"
.format(most_common_room_number(dane))) .format(most_common_room_number(dane)))
print("{} to najłądniejsza dzielnica w Poznaniu." print("{} to najładniejsza dzielnica w Poznaniu."
.format(find_borough("Grunwald i Jeżyce")))) .format(find_borough("Grunwald i Jeżyce")))
print("Średnia cena mieszkania 3-pokojowego, to: {}" print("Średnia cena mieszkania 3-pokojowego, to: {}"
.format(mean_price(dane, 3))) .format(mean_price(dane, 3)))