Python Series

Data Analysis with pandas for Finance and Accounting Welcome to post #12 in our Python journey! In the previous post, we explored NumPy and its powerful numerical capabilities. Now we’re taking a step up to pandas, which builds on NumPy’s foundation to provide specialised tools for working with tabular and time series data—exactly the kind of data we deal with daily in finance and accounting. Why pandas for Finance? pandas is specifically designed for data analysis and manipulation, with particular strengths in: ...

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. ...

Command-Line Tools & Automation in Python I’ve discovered that some of the most practical Python applications aren’t fancy data visualisations or machine learning models, but rather simple automation scripts that save time on repetitive tasks. In this post, I’ll walk through how to build command-line tools and automate everyday processes using Python. Building Command-Line Scripts with argparse When you’re working with financial data, you often need flexible tools that can handle different inputs. The argparse module lets you build command-line scripts that accept various arguments and options. ...

Testing & Debugging: Building Reliable Financial Tools When working with financial data and calculations, accuracy is essential. A small bug in your code could mean reporting incorrect figures, making flawed investment decisions, or even compliance issues. This post will guide you through testing and debugging techniques that ensure your financial Python code works correctly and reliably. Why Testing Matters in Finance Imagine you’ve created a Python script that calculates loan amortisation schedules. Your company uses this tool to price thousands of loans. If there’s an error in your interest calculation logic, even a small one, the financial impact could be enormous. ...