12-03, 16:30–17:00 (UTC), Talk Track II
The International Monetary Fund (IMF) provides a huge variety of economic datasets from different countries. We have explored the Python API for data extraction from the IMF, which allows users (primarily economists or financial analysts) to access the data. The structure of the underlying JSON datasets is quite complex for an unprepared user. In the talk, we will demonstrate the API workflow and go over the issues that we are designing a new, easier-to-use API, which is currently being developed. This is joint work with Dr. Sou-Cheng Choi (Illinois Institute of Technology and SAS Institute Inc.).
The talk is primarily directed at data analysts and economists interested in utilizing IMF's macroeconomic data.
The International Monetary Fund (IMF) is an international organization that provides financial assistance and advice to member countries. Out of 195 countries in the world, 190 are members of the IMF. Apart from advising services, the IMF collects large amounts of data on various economic indices from its member countries. The data can be accessed using a web interface or a Python API. In the summer of 2022, I worked on an internship with Prof. Sou-Cheng Choi at the Illinois Institute of Technology. While using the Python API, we realized that it is not exactly intuitive for first-time users, for whom it could easily take more than a few days to figure out the right way to download a target economic time series. The main issue is that the data is stored in layers of datasets called series, with each series containing multiple dimensions. For example, to find a country's Consumer Price Index (CPI), one would need to first discover the correct names of the containing series and dimension, followed by a text search of well-selected keywords. We will demonstrate the API so that more people can access the data. Currently, we are designing a new approach to pulling data from the IMF, which we believe will be more intuitive, especially for beginning or non-technical users such as data scientists. This presentation should be of interest to anyone who has ever had to work with international economic data. To demonstrate the API, we will be using Python and Jupyter Notebooks.
Link to the description of the API: https://datahelp.imf.org/knowledgebase/articles/1968408-how-to-use-the-api-python-and-r
No previous knowledge expected
MAS Data Science, Illinois Institute of Technology