What’s next#


The contents of Gurobi Finance are distributed under the Apache License 2.0, meaning you can use, read, and modify the code freely within the license terms. However, it depends on a commercial package (gurobipy) that requires a license. When installed via pip or conda, gurobipy ships with a limited trial license for the Gurobi Optimizer that handles models of limited size. For the examples here, you will typically need a full-featured license, for which you have two options:

  • If you are a commercial user: please visit https://www.gurobi.com/free-trial/ to request a full-featured Evaluation License, which will allow you to use datasets of unrestricted size in the notebooks of Gurobi Finance.

  • If you are an academic user: Gurobi provides free licenses for faculty members, students and staff at recognized academic institutions. In most cases, you can generate a license yourself through the self-service feature of the Gurobi user portal. Please see How do I obtain a free academic license? for further instructions.

Portfolio OptiMod#

You’ll find many of the features discussed here in an integrated, data-driven interface in the Mean-Variance Portfolio OptiMod.


gurobipy-pandas is a convenient (optional) wrapper to connect pandas with gurobipy. It enables users to build mathematical optimization models more easily and efficiently from data stored in Pandas DataFrames and Series, and to read solutions back directly as pandas objects.

gurobipy-pandas 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.