I'm a resource economist with a passion for data analysis and technology. Over the past few years, I've watch the development of the data science field and I've become increasingly interested in the subject. Data science seems to complement the tools economists use to understand how humans allocate scarce resources. While econometrics tries to fit data to economic models, data science can help fill in the gaps between economic theories and may even help discover new economic models. My goal is master these new techniques of data science and share them with you here on this site.

I will be primarily working in the Python programming language. While I've used R in the past, I've come to discover that the general flexibility and scalability of Python will likely make it the dominate platform for conducting data science. Therefore, I've spent the past year learning Python. One of my favorite resources for getting up to speed with Python has been the book, Automate the Boring Stuff with Python by Al Sweigart. After figuring out the basics of Python programming, I've moved on to Pandas, Folium, Requests, Selenium, Matplotlib, NLTK, Numpy, and Scikit-learn. It seems like I find a new interesting Python libraries every week now. This is quite a shift from my traditional economic toolset of Excel, SAS, SQL, and ArcGIS to get my work done.

Ultimately, I hope to blend my background in economics with the new techniques in data science to create some whole new methods for using data to learn about the world. Maybe I'll become a Data EconoScientist along the way.

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