Gurobipy Pandas is our convenient wrapper library to connect pandas with gurobipy. It enables users to efficiently build mathematical optimization models from data stored in DataFrames and Series and extract solutions as pandas objects.
This project is aimed at experienced pandas users who are familiar with methods to transform, group, and aggregate data stored in dataframes. It expects some familiarity with optimization modeling, but does not require deep experience with gurobipy.
 Webinar: Building Gurobi Models from Pandas Dataframes
As the de-facto standard in Python for data manipulation and analysis, pandas is deeply integrated into many analytics projects and tools. Gurobi’s Python API, gurobipy, does not directly interact with standard pandas data structures, so incorporating decision optimization into data science applications is not as straightforward as it could be. For better interoperability between the two libraries, what is needed is a higher-level syntax to build optimization models directly from suitably structured pandas data. Our solution is gurobipy-pandas, a convenient wrapper library to connect pandas with gurobipy. Watch this webinar to so how it enables users to efficiently build mathematical optimization models from data stored in DataFrames and Series, and to extract solutions as pandas objects. This webinar will walk through basic concepts and complete modeling examples to demonstrate best practices for using this library. Watch the webinar, “Building Gurobi Models from Pandas Dataframes.” |
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