Exploratory Data Analysis (EDA)
Case Study: Housing Price Prediction
The most difficult part on pricing a house is that, there are many variables that involved. Those may include locations, year the house built, accessability to the public places, and so on. The end goal is to predict the sales price for each house. For each ID in the test set, you must predict the value of the SalePrice variable.
But for this class, we will just perform Exploratory Data Analysis.
Data was taken from this Kaggle website for our learning purpose on IYKRA DATA MBA Program. Here is the link source:
https://www.kaggle.com/c/house-prices-advanced-regression-techniques.
Data contains 79 variables which can be seen the description here:
https://www.kaggle.com/c/house-prices-advanced-regression-techniques/data