Overview, summary, and practical exercises on the main topics of Python programming for Data Science.

This repository aims at being a compilation of resources to guide you during the Programming for Data Science classes. You can use it as one two ways:

You can use your global/default Python environment installed with Anaconda and focus on the jupyter notebooks inside the notebooks folder.

If you try to run the written code and have any errors regarding package version conflits, please look at what version of the problematic package this project uses in the pyproject.toml config.

In this method, instead of using the global Python environment in your machine, you can create an independent virtual environment using pyenv with the required specifications for this project.

To do so, please follow the steps in the Development environment chapter bellow.

For the Jedi users.

Requirements:

• pyenv (Python version management)
• poetry (Python dependency management)

$ pyenv install 3.11.1
$ poetry install

Vitor Manita ([email protected])