Data Science

NumPy Fundamentals for Numerical Data (with Finance Applications) Welcome to post #11 in our Python learning journey! If you’ve been following along, you’re starting to build a solid foundation in Python. Now it’s time to explore NumPy, the powerhouse library that makes Python a serious contender for numerical computing and data analysis. As a finance professional myself, I’ve found NumPy particularly useful for financial calculations, portfolio analysis, and working with large datasets. Let’s dive in and see how this library can level up your Python skills. ...

The Python Ecosystem & Interactive Data Workflows As a finance professional diving deeper into Python, I’ve found that understanding the broader ecosystem of tools is just as important as learning the language itself. In this post, we’ll explore the different ways to manage Python packages and environments, and dive into interactive data workflows that can transform how you work with financial data. Package vs. Environment Managers: pip, conda, and Anaconda When I first started with Python, I was confused by the different tools available for installing packages and managing environments. Let’s clarify these concepts. ...