This repository contains notebooks and code for analysing data published to the Beneficial Ownership Data Standard (BODS). The work contained here has been produced as part of the Opening Extractives programme which is implemented jointly between the Extractive Industries Transparency Initiative International Secretariat and Open Ownership.
The main components are:
-
A Python module
qbods.py, which contains a set of functions for reading, summarising and analysing BODS data. This code is under development and will likely contain bugs. -
An iPython notebook
latvia_demo.ipynb, which contains code to run a subset of the functions on an initial dataset released by the Register of Enterprises of the Republic of Latvia, with accompanying text.
Additional notebooks will be added to the repository as this work progresses.
Clone the repository, open the notebook in a suitable program (e.g. VS code), and follow setup instructions within the notebook.
To run on Deepnote, clone this repository, then create a new project and upload the notebook, alongside qbods.py and requirements.txt as files. Then open the notebook and follow setup instructions.
To run on Google Colab, clone this repository, then click File > Upload notebook, and upload the notebook. Then in the left hand menu, click on icons for 'Files' then 'Upload Files', then upload the files qbods.py and requirements.txt. Then open the notebook and follow setup instructions.
Suggestions for new queries and contributions are welcomed via issues and pull requests, respectively