Germany Rental Housing Prediction 🏘️📈

Introduction 🌟

Housing Crisis in germany is getting grave.
The country’s current government wants to create an entirely new ministry to oversee it.
Government pledge is to built 50,000 more units than the current goal.
Berlin tried to cap rents for five years, but court threw out the law earlier last year.
Germany has 1.8 million empty apartments, according to the DStGB, outside cities where people are less interested in living.
Population growth, bad decisions, slow construction, competing demands: These are just some of the causes of Germany's housing crisis

The data is obtained from “Kaggle” for this project.
The data was scraped from Immoscout24.
The data set contains most of the important properties, such as living area size, the rent etc.
The dataset has 49 Columns and 268850 Rows.
Data could be found at https://www.kaggle.com/corrieaar/apartment-rental-offers-in-germany

Data cleaning to clear the outliers and remove columns that doesn't have high correlation to the prediction
Create visualization to have a better understanding of the rental properties in Germany.
Try to Answer some pressing questions.
Feature engineering from the original variable to create a better model
Create a tool that estimate the house cost predicted by many variables
Compare those model to see the best results.