Mar 2023 - Supercharge your Python Dev Environment with VS Code & XGBoost Wage Prediction Model

Philly Python Users' Group + DataPhilly collaboration in-person event on Wharton's campus (Philadelphia, PA) on Mar 30, 2023.

Supercharge your Python Development Environment with VS Code
Dawn Wages
VS Code is a free code editor, built on open source, runs everywhere, and is made to be extensible for your development environment. Regardless of your workflow, you're able to modify your Python supporting tools and extensions so you can focus on the code. This talk is broken up into three sections: features for collaboration, code editing, and content creation.
VS Code supports the open specification for Dev Containers which lets you use a Docker container as a full-featured development environment. You can open any folder or repository inside the container and take advantage of all the features in Visual Studio Code starting with a devcontainer.json. I'll show you how to create a Dev Container, how to share it, and the ways that it expedites the process of jumping into a new project, quickly making a change, and proposing a PR. In this Dev Container, I'll show some of my favorite extensions for code development including but not limited to: ruff the Python linter, Black the Python formatter, Jupyter notebooks, and Python extension IntelliSense. And finally, I'll show you how these specifications, as well as some options for UI, can make it easier to give demos, stream, teach or just make your IDE pretty.

Bio: Dawn Wages (she/her) is a Python and Django engineer, Open Source Software contributor, and Python Community Advocate at Microsoft.

XGBoost Wage Prediction Model Based on 2021 Immigration Data
Paul Chan
The US labor department uses local US wage demographics to assess the wage of foreign workers. It is to determine if the local employers have been abusing foreign workers or intentionally providing lower than market salaries to the foreign workers to avoid hiring local US residents and citizens. The data used in this study are the data related to Permanent cases, whose approval is the first step of employer-sponsored green cards. Due to the complexities of the features in the prediction model, a more complex and gradient-boosted decision tree model, XGBoost, is used for this purpose.

Bio: Paul Chan is a safety engineer for industrial control systems. He works with industrial data and manages risks in the context of reliability engineering. He is originally from Hong Kong but moved to the US about 5 years ago.