Exploratory data analysis of socially responsible investment opportunities into real estate of King County (WA, USA)

The names and personalities below are fictional.

The challenge

Ms. Erin Robinson - The Client of Nova Piscibus Consulting GmbH - is a socially responsible investor in the real estate. She wishes to improve living conditions in King County (WA, USA) by investing into the development of poor neighborhoods. Our goal at Nova Piscibus is to determing the factors that affect potential returns and are aligned with the Client's.

The dataset

The dataset consists of Price of Houses in King County, Washington from sales between May 2014 and May 2015 and was provided by @neuefische. Along with the house sale history, it provides the information on 18 house features, such as house area, lot area, location, etc. (see full description inside the main document).

Navigation

• Data cleaning
• Analysis

❗️The notebooks will not run without the file data/houses.csv. The dataset used here can be reconstructed from the the house_data and house_sales datasets on Kaggle - with a little bit of effort and no guarantee of reproducibility.

Result summary

Nothing affects the price more than

• the proximity to Seattle downtown
• the living area in the house.

Based on extensive data exploration, I suggest the following three objects:

	id	bedrooms	bathrooms	m2_living	m2_lot	floors	waterfront	view	condition	grade	m2_above	m2_basement	yr_built	yr_renovated	zipcode	lat	long	m2_living15	m2_lot15	sale_date	price	basement_share	age	yrs_since_renovation	p_per_m2	dist_from_center	zone	poor_neighborhood_id
69	2648500030	1	1	100.334	300.074	1	0	0	3	6	100.334	0	1963	nan	98002	47.3075	-122.217	112.412	535.117	2014-07-25	112000	0	52	nan	1116.3	61.3488	rural	0
24	2781250750	2	2	126.347	306.577	2	0	0	3	6	126.347	0	2004	nan	98038	47.3489	-122.022	121.702	306.577	2014-08-28	222000	0	11	nan	1757.1	53.9958	rural	13
91	5560000650	3	1	141.211	785.024	1	0	0	2	6	104.051	37.1609	1961	nan	98023	47.328	-122.337	122.631	785.024	2014-12-02	135000	0.263158	54	nan	956	57.5993	rural	20

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For development

Setup the local environment

macOS or Linux:

• Install the virtual environment and the required packages by following commands:

  pyenv local 3.11.3
  python -m venv .venv
  source .venv/bin/activate
  pip install --upgrade pip
  pip install -r requirements.txt

Windows:

• Install the virtual environment and the required packages by following commands.

  For PowerShell CLI :

  pyenv local 3.11.3
  python -m venv .venv
  .venv\Scripts\Activate.ps1
  pip install --upgrade pip
  pip install -r requirements.txt

  For Git-Bash CLI :

  pyenv local 3.11.3
  python -m venv .venv
  source .venv/Scripts/activate
  pip install --upgrade pip
  pip install -r requirements.txt