In this analysis, we delve into a comprehensive analysis (made with R) of living costs across 4500 cities worldwide. The data has been scraped from Numbeo and can be found on Kaggle. The primary goal of this project is to gain familiarity with R and R Studio, and learn how to extract meaning from relatively large datasets. As such, it isn't important whether the data points are real or not.
Our journey begins with an exploratory data analysis (EDA) of the dataset. This initial phase aims to uncover various patterns and insights, all of which are detailed in the eda.Rmd file.
Moving forward, we proceed to calculate the Cost of Living Index (COLI), facilitating a holistic comparison among the diverse cities. For a detailed breakdown of our COLI analysis, refer to the coli.Rmd file.
The next step is to look at how living costs compare globally to determine the factors that influence specific price strategies around the world. Furthermore, we evaluated basic costs and salaries by country and capital to figure out the affordability of essential needs. The Living costs globally.Rmd file contains all of the details.
In our concluding phase, we delve into an insightful comparison between developed and developing countries, check develop_vs_developing.Rmd file.
Join us as we navigate through the intricacies of statistical analysis and unveil meaningful insights into global living costs.
Note: this was a collaborative task with other two peers in the international BABD master @ POLIMI General School of Management.