Resources

This page collects resources for our team to use and learn from. We onboard new students nearly every semester, they learn to code in R, Python, etc. and can find useful learning guides for that here (thanks to Prof. Kalinowski of Quinnnipiac's Economics and Data Science program).

Our team primarily uses the following databases:

US Federal Reserve's FRED Database
- You don't need the API in R. You can use library("quandl") and the "get" function.
YahooFinance
- You can use library("quandl") and the "get" function.
GoogleFinance
- Use get.price.google(tkr, bg = "2001-01-01",ed = "today") with arguments tkr for company ticker, e.g. "BABA","AMZN" and bg for beginning date, e.g."2000-02-29" and ed for ending date, e.g. "today", "2016-11-10"
DBNomics
- This is a collection of multiple databases. There's a lot there, but it can be very cumbersome and complex if you don't know exactly where to find what you want.
- install.packages("rdbnomics") and library(rdbnomics)

Additional Options

International Monetary Fund's International Financial Statistics (IMF - IFS)
- This is a large database with the most current data the IMF has. It's good for monthly, quarterly and annual. There is an api for R, install the following and use the library: install.packages("imf.data") and library(imf.data).

Prof. Ball's personal website has links for other data sources for broader research.

https://www.chrisball.us/economics-resources

R for Data Science

This has been our go-to website/book for learning R. We recommend people start by following the book 100% for the first 3 chapters. It's fun and easy, but take your time and don't skip, and by the time you finish, you'll be able to do all sorts of basic graphs. The next big hurdle is making it through Chapter 5 which covers basic data manipulation. After that, you can skip around a bit and learn as needed, combine with Goolge or ChatGPT questions. Here's the URL: https://r4ds.had.co.nz/.

Python for Data Analysis, 3E

This is a new book for the team. We started in R but are now expanding to Python. This is the top recommendation for starting data analysis in Python. Here's the URL: https://wesmckinney.com/book/

ggplot2: Elegant Graphics for Data Analysis (3e)

This book is helpful in understanding and expanding your ability to make graphs in R. The URL: https://ggplot2-book.org/index.html

R Programming for Data Science

This book was helpful to me (Chris Ball) for understanding mathematical manipulations in R. The URL: https://bookdown.org/rdpeng/rprogdatascience/

Elementary Statistics with R

This book was helpful to me (Chris Ball) for understanding some basic statistics (more mathematical statistics) in R. The URL: https://homerhanumat.github.io/elemStats/

Forecasting: Principles and Practice (3rd ed)

This book was helpful to me (Chris Ball) for understanding some basic time series in R. It's called "forecasting" but that's basically an application using time series. So I think of this as a good intro time series in R book. The URL: https://otexts.com/fpp3/