Hi everyone,

I am a researcher at  Development Data Lab <https://www.devdatalab.org/>  and 
I wanted to share a Py package I recently created for our data workflows: 
*AdminLineageAI*.

The package helps create crosswalks between administrative units across 
datasets and time periods using Artificial Intelligence. For example, 
matching districts, subdistricts, states, or countries when names differ 
because of spelling variants, translations, renaming, splits, or mergers.

This problem comes up often in research and policy datasets. For example, 
one dataset may use *Paschimi Singhbhum* while another uses *West Singhbhum*
, *Allahabad -> Prayagraj* or a newer district may be split from its older 
predecessor district. These cases are difficult to solve with plain fuzzy 
matching.

Some possible use cases include matching government scheme data to Census 
or official administrative lists, creating district or sub district 
evolution crosswalks across years, handling renamed/split/merged 
administrative units, and building reproducible data pipelines for social 
science, policy, or development research.

It is experimental, so important matches should still be cross-checked but 
I would love to hear more possible use cases for it. Main aim here is to 
reduce manual work spent on just merging dataset.

You can install it with:

*pip install adminlineage*

Here  <https://github.com/TahaIbrahimSiddiqui/AdminLineageAI>is the GitHub 
repo with usage instructions and a few examples:

It is open source, so please feel free to fork it, use it, or raise an 
issue on GitHub if you have feedback or run into anything.

Best,

Taha 

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