City Savings is a project designed to help users identify the most financially beneficial city to reside in, considering specific factors over a 20-year period. By leveraging a combination of economic data and advanced algorithms, CitySavings enables users to make informed decisions about where to live to optimize their savings and investments. Project Description:
City Savings Analyzer: A Python project that helps you find the city with the best savings potential over a 20-year period, considering various factors. Compare cities like "San Francisco", "New York", "Boston", "Oakland", "San Jose", "Los Angeles", "Washington", "Seattle", "San Diego", and "Miami" to determine the most financially advantageous option for you.
Factors considered:
Rent in each city Standard yearly salary ($48,000) Monthly bonus (3/10 of the monthly rent) for the first two years Grocery expenses (1/100 of the monthly rent) Current location (Boston) Relocation fee ($10,000) applicable for all cities except Boston One-time relocation allowed, with a minimum stay of one year in each city How it works: The Python code takes the above factors into account and calculates the total savings over a 20-year period for each city. It factors in rent, bonuses, grocery expenses, and relocation fees to provide a comprehensive analysis. The cities will be listed in descending order based on their potential for savings.
Note: This project includes a plotting function to visualize the savings data for easier comparison between cities.
To compare human and AI responses, we used OpenAI's ChatGPT to gather feedback on city choices, factors, and preferences for savings analysis. The responses were then compared with human inputs to evaluate the effectiveness and accuracy of the AI model in guiding users towards the best financial decision.