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# System prepended metadata

title: Data Exploration

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# Data Exploration
- Features Available
- Missing Values
- House prices kernel estimation per geographic coordinates
- Price distribution per building area
- Average house price per year built
- House price distribution per region

# Feature Eng
- Pegar no Address e separar por Address Name
- Date, separar por Day, Month, Year.

# Data Preparation
# Modeling
- Regression Trees
- Bagging
- Random Forest
- Boosting
- Kernel Approaches (SVM)

# Dataset
(https://www.kaggle.com/anthonypino/melbourne-housing-market)

- Suburb: Suburb
- Address: Address (eliminar)
- Rooms: Number of rooms
- Price: Price in Australian dollars
- Method:
    - S - property sold;
    - SP - property sold prior;
    - PI - property passed in;
    - PN - sold prior not disclosed;
    - SN - sold not disclosed;
    - NB - no bid;
    - VB - vendor bid;
    - W - withdrawn prior to auction;
    - SA - sold after auction;
    - SS - sold after auction price not disclosed.
    - N/A - price or highest bid not available.
- Type:
    - br - bedroom(s);
    - h - house,cottage,villa, semi,terrace;
    - u - unit, duplex;
    - t - townhouse;
    - dev site - development site;
    - o res - other residential.

- SellerG: Real Estate Agent
- Date: Date sold
- Distance: Distance from CBD in Kilometres
- Regionname: General Region (West, North West, North, North east …etc)
- Propertycount: Number of properties that exist in the suburb.
- Bedroom2 : Scraped # of Bedrooms (from different source)
- Bathroom: Number of Bathrooms
- Car: Number of carspots
- Landsize: Land Size in Metres
- BuildingArea: Building Size in Metres
- YearBuilt: Year the house was built
- CouncilArea: Governing council for the area
- Lattitude: Self explanitory
- Longtitude: Self explanitory

