housing_model's People
housing_model's Issues
CSV should write some sort of NULL value for displaced people
I think that the generate_csv output method should output some NULL (whatever excel uses?) instead of nothing.
current csv output:
min_score,max_rent,rent,apt_score
4,558,0,
better csv output:
min_score,max_rent,rent,apt_score
4,558,0,NULL
error with mismatched sizes
I'm trying to simulate these 17 renters and 12 houses, but I get an error:
> python simulate.py
input number of renters with minimum housing score 1: 10
input number of renters with minimum housing score 2: 2
input number of renters with minimum housing score 3: 2
input number of renters with minimum housing score 4: 2
input number of renters with minimum housing score 5: 1
input number of housing units with score 1: 3
input number of housing units with score 2: 3
input number of housing units with score 3: 3
input number of housing units with score 4: 3
input number of housing units with score 5: 3
Traceback (most recent call last):
File "simulate.py", line 41, in <module>
user_input()
File "simulate.py", line 27, in user_input
mod = model.HousingModel(renters, houses)
File "/src/housing_model/model.py", line 15, in __init__
hm.stable_match(self.renters, self.houses)
File "/src/housing_model/house_match.py", line 30, in stable_match
for house in sorted(random.sample(houses, k), reverse=True):
File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/random.py", line 321, in sample
raise ValueError("sample larger than population")
ValueError: sample larger than population
Not enough people who will accept quality 1 housing
Economic Factors
Anyone have thoughts on tying the number of renters (and their ability to pay) to a function representing the state of the economy? This could allow us to explore how economic booms and busts tie into the demand for housing.
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