Repository for ifohack 2023. Team: Aziz, Joey, Zelda, Leo and Max.
#Outline of our project. We tried to find the most relevant Variables to predict land prices in Berlin. We ended up defining
- Population
- Population under 30
- The restaurant rate per 10000 persons
- Crime rate per 1000 person
- Vacant Buildings
We found the population, the population under 30, and vacant buildings in the data set provided. We calculated the crime rate and the restaurant rate after finding the number of crimes from 2019 we matched street names to neighborhoods to get the data of the crimes and then (Berlin Kommisariat) and the number of restaurants (open street maps) and calculating the number by neighborhood the restaurant rate is for 10000 people living in the neighborhood the crime rate is per 1000 people living in the neighborhood.