In today's world where working remotely is becoming a fast norm, finding a city that you can call home hinges not only on your job location and affordability. Factors like happiness, population, pollution index, etc. are becoming more and more relevant. This tool helps people to choose a city depending on their likes and dislikes, which they can call home.
How I built it
We used Pandas, a Python library, to analyze the Movehub dataset and figure out what factors come into play when people decide where to live.
What I learned
Although we only focused on a subset of variables, it becomes clear that no single variable is the determining factor when people decide where to live. For example, the Movehub Rating, which summarizes the overall appealingness of a city correlates rather loosely with the crime rate and a pattern isn't really clear, which demonstrates that other factors are very important. On the other hand, there appears to be a fairly strong linear correlation between quality of life and cost of living index. The graph appears as a blob, but there is a pattern. In particular, we can assume that ~80% quality of life stronly correlates with a cost of living index of 60-80.