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ZILLOW HOUSE PRICE PREDICTION GROUP MEMBERS: LINGZI HONG PRANALI SHETTY.

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Presentation on theme: "ZILLOW HOUSE PRICE PREDICTION GROUP MEMBERS: LINGZI HONG PRANALI SHETTY."— Presentation transcript:

1 ZILLOW HOUSE PRICE PREDICTION GROUP MEMBERS: LINGZI HONG PRANALI SHETTY

2 DATA COLLECTION ZILLOW (BASE DATA): WE SCRAPED THE DATA FROM ZILLOW, WHICH IS A HOME AND REAL ESTATE MARKETPLACE WITH DATA ABOUT THE RECENT HOUSE PRICES. CITY: SEATTLE, WA ZILLOW ALSO HAS DATA ABOUT HOUSES ON SALE, RENT, ALREADY SOLD, FORECLOSURE ETC. FOR THE SCOPE OF OUR PROJECT, WE CHOSE THE HOUSES THAT WERE ALREADY SOLD FOR PREDICTION. THEY INCLUDE VARIOUS TYPES OF HOMES LIKE CONDOS, TOWNHOUSE, HOUSE, APARTMENTS ETC. WE CHOOSE HOME TYPE ‘HOUSES’

3 DATA PROPERTIES SCRAPED ABOUT 1737 HOUSES ‘FOR SALE’. SCARPED ABOUT 6878 HOUSES ‘SOLD’. ATTRIBUTES: HOUSE SOLD DATE, BED, BATH, SQUARE FEET AREA, ZILLOW ESTIMATE (THE PRICE ZILLOW ESTIMATED), PRICE, PRICE/SQFT, LOT AREA, ADDRESS, LOCALITY, REGION, YEAR HOUSE WAS BUILT.

4 FEATURES ADDED SCHOOL, ENVIRONMENTAL DATA, TRANSPORT DATA, CRIME DATA, MEDIAN AGE PER ZIPCODE, MEDIAN INCOME PER ZIPCODE WERE SOME OF THE FEATURES WE DECIDED TO ADD. SCHOOL DATA: API: SCHOOLSEARCH NEIGHBORHOOD DATA: DATASET OBTAINED FROM SEATTLE.GOV CRIME: DATASET OBTAINED FROM SEATTLE.GOV MEDIAN AGE: USED THE US CENSUS DATA (2010) API MEDIAN INCOME: USED THE US CENSUS DATA (2011) API

5 HOW DATA WAS MERGED SCHOOLS WITHIN 1KM OF EACH HOUSE (NUMBER OF SCHOOLS AND DISTANCE OF NEAREST SCHOOLS) NEIGHBORHOOD PARAMETERS WITHIN 0.5KM OF EACH HOUSE (NUMBER OF SCHOOLS AND DISTANCE OF NEAREST ATTRIBUTE) NUMBER OF CRIMES WITHIN 3KM OF EACH HOUSE MEDIAN AGE AND MEDIAN INCOME WERE MAPPED ON ZIPCODE

6 GENERAL PLOTS

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9 THANK YOU


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