I use Python’s data analysis libraries to investigate and make sense of economic data, and use Plotly and D3 to visualise what I find. My blog posts tend to fall into three categories:
- Data Carpentry – the process of loading data and manipulating it into a form that allows for easy analysis.
- Data Visualisation – how to display the data in an attractive way that allows people to gain insight and knowledge.
- Using Python – short posts that explore a specific aspect of data analysis and how to accomplish this with the Python data analysis libraries.
In each blog post, I try to explain my methods of analysis and visualisation as well as my reasoning behind them. I hope that this is a helpful resource, and that you can apply my ideas to your own analyses. In every case, please take my code, use it, reuse it, rewrite it and utilise it however you wish!
Please get in touch if you have any requests for analysis or visualisation techniques, any comments on my work, or any suggestions for how I could improve this site; I’d love to here from you!