dariodip/rfd-discovery
This project, written in Python and Cython, deals with Discovery of Relaxed Functional Dependencies(RFDs) using a bottom-up approach.
This tool helps data analysts and database administrators understand the hidden relationships within their datasets. You provide a CSV file, representing a table from a relational database, and it outputs "Relaxed Functional Dependencies" (RFDs). RFDs reveal how closely columns are related even if they don't follow strict database rules, like finding that 'city' often determines 'state' but with some slight variations.
No commits in the last 6 months.
Use this if you need to uncover flexible, probabilistic relationships between columns in your tabular data without having to pre-define strict thresholds.
Not ideal if you need to enforce strict, exact functional dependencies, as this tool focuses on discovering "relaxed" or approximate relationships.
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Language
Python
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Last pushed
Mar 17, 2021
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