Welcome to wrighters.io!
My name is Matt Wright and I write articles that help you learn more about programming and working with data in Python. My focus is on some of the more popular Python libraries, including pandas, Jupyter, Matplotlib, and Numpy. I also focus on measuring and improving performance, various programming topics, and finance.
Indexing in pandas
Understanding pandas indexing can be a challenge. Start here to learn all about it, starting with the basics. You can also download my free ebook for all the info (plus a few extras) in one convenient package.
Python is commonly used in finance for time series analysis, web scraping, and visualization. These articles cover a number of common finance use cases.
Profiling and Performance
Details on some tools and techniques for getting the best performance out of Python.
How to view all the variables you’ve created in a Jupyter notebook.
Papermill is an excellent library for adding parameters to notebooks. I show you a complete example of how to set it up and use it to automate a task.
Indexing time series data in pandas is similar to regular indexes, but there are fundamental differences.
Unit testing Jupyter notebook code is not only possible, but can be quite useful.
Python and pandas are useful tools for analyzing financial data, such as looking at stock data near events.