A Practical Guide to Macroeconomic Data with R and Python
(Click on the cover image of the version that you would like to explore!)
As the names of these books imply, we aim to equip the reader with practical tools, code and data to analyze the Macroeconomy.
Macroeconomic data measure a country’s income, consumption, employment, imports and exports, monetary policy, interest rates and, inflation among other related data. Macroeconomic data are important to understand the health of the aggregate economy. News or updates about the macroeconomic indicators can also have significant impact on stock returns, bond returns and other asset markets.
We use two programming languages, R and Python, as tools to understand and analyze this data.
As the two books and code show, these popular programming languages have their own advantages and disadvantages. Both are essential tools in an analyst’s tool kit.
By these books’ end, you will have the tools that you need to hit the ground running as a macro data scientist. These books are focused on modern data science and practical tools for everyday use. We include many data visualizations in this book, along with the details of how to build them. These serve as a launch point for your own creativity. We believe strongly in the power of visualization and after reading this book, you should have the tools you need to imagine, build and deliver very effective messages using data.
These books broadly take the first steps in a quantamental approach to finance and investing, the idea being to combine fundamental analysis with quantitative analysis. In this context, top level quantitative analysis starts with macroeconomic data.
Some of the economic indicators we consider are GDP growth, interest rates, inflation, employment, housing and foreign exchange rates.
To learn more about the books visit
We thank Kosha Bheda for the cover design.
We greatly appreciate any feedback that you may have on the book. We plan to revise the book regularly by incorporating reader feedback. Let us know if you would like to see any additional macroeconomic indicators included in the book or if you have any other feedback on the exposition, code, or any other aspect of the book. Your input is valuable to us. We will acknowledge readers who have given significant constructive feedback in the next version of the book. You can send feedback to the following email addresses:
- For the Python version of the book, email: macro-python@quantseer.com
- For the R version of the book, email: macro-r@quantseer.com
