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We created an interactive web application in Python for determing the best states to live in based on user preferences. We sourced data from the FRED Economic Database with custom API wrappers and integrated it into a Python Dash Application framework. Users can filter states, data catageories and even apply weights to parameters for use in the …

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wyattm94/Interactive-Application-for-ranking-US-States-in-Python

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Interactive Application for ranking US States in Python

This project is an interactive application for users to set parameters and filters across US state-wide data to help them determine which were the top states to live in based on their preferences. We designed a custom protocol for calling the FRED economic database API to collect all state-based data sets and through an algorithm for cross-referencing and filtering, we created cleaned data sets that uniformily covered all 50 states with the highest level of granularity. The data sets were then loaded to populate the frontend interface, which is built on the Python Dash module. This allowed us to create a multi-level, web-based, interactive application where the users can filter results by data set and US state, and apply weights to their preferences. We created a series of custom elements and callbacks, which wrapped around the core framework, to accomodate these tasks. The user can simply update the calculations and rankings as they change their preferences which also updates a geographically correct heatmap of the US to show relevant ranks across all 50 states.

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We created an interactive web application in Python for determing the best states to live in based on user preferences. We sourced data from the FRED Economic Database with custom API wrappers and integrated it into a Python Dash Application framework. Users can filter states, data catageories and even apply weights to parameters for use in the …

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