Amsterdam House Price Prediction
Predict Sales Prices and Practice Feature Engineering
@kaggle.thomasnibb_amsterdam_house_price_prediction
Predict Sales Prices and Practice Feature Engineering
@kaggle.thomasnibb_amsterdam_house_price_prediction
If you are like me, you might get overwhelmed when having to make big decisions such as buying a house. In such cases, I always like to go for a data driven approach, that will help me find an optimum solution. This involves two steps. First, we need to gather as much data as we can. Second, we need to define a metric for success.
Gathering housing prices requires some effort. A caveat is that the asking prices are not the prices to which the houses were actually sold. Defining a metric for success is somewhat subjective. I consider a house to be a good option if the house price is cheap compared to other listings in the area.
The housing prices have been obtained from Pararius.nl as a snapshot in August 2021. The original data provided features such as price, floor area and the number of rooms. The data has been further enhanced by utilising the Mapbox API to obtain the coordinates of each listing.
Thanks to Pararius
CREATE TABLE housingprices_amsterdam_august_2021 (
"unnamed_0" BIGINT -- Unnamed: 0,
"address" VARCHAR,
"zip" VARCHAR,
"price" DOUBLE,
"area" BIGINT,
"room" BIGINT,
"lon" DOUBLE,
"lat" DOUBLE
);
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