pdhs - A package for managing and analyzing Demographic and Health Survey (DHS) data

[adejumoridwan]

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Package Info

Submitting Author: Adejumo Ridwan Suleiman (@learndataxyz)
Repository Link (if existing): https://github.com/learndataxyz/pdhs

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• Paste the full DESCRIPTION file inside a code block below:

Access to high-quality, structured, and timely demographic and health data is essential for researchers, policymakers, and public health professionals. The [Demographic and Health Surveys (DHS) Program](https://www.dhsprogram.com) provides a rich repository of standardized datasets across countries and years. However, accessing and using this data programmatically can be cumbersome due to inconsistencies in interfaces, authentication requirements, and data formatting.

The `pdhs` Python library aims to streamline and simplify interaction with the DHS API. It offers an intuitive, well-documented, and Pythonic interface for querying, retrieving, and managing DHS datasets. By abstracting low-level API complexities, `pdhs` allows users to focus on analysis and application rather than on data wrangling. It supports reproducible research, integrates smoothly with common data science workflows (e.g., pandas, numpy, matplotlib), and promotes broader usage of DHS data in academic, development, and policy contexts.

> In short, `pdhs` bridges the gap between powerful public data and the tools needed to derive meaningful insights from it.

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`pdhs` is a package for managing and analyzing [Demographic and Health Survey (DHS)](https://www.dhsprogram.com) data. It provides functionality to:

1. Access standard indicator data (via [DHS STATcompiler](https://www.statcompiler.com)) using the [DHS API](https://api.dhsprogram.com/).
2. Identify surveys and datasets relevant to specific analyses.
3. Download survey datasets from the [DHS website](https://dhsprogram.com/data/available-datasets.cfm).
4. Load datasets and associated metadata into Python.
5. Extract variables and combine datasets for pooled multi-survey analyses.

• Please indicate which category or categories this package falls under:

  • Data retrieval
  • Data extraction
  • Data munging
  • Data deposition
  • Data visualization
  • Reproducibility
  • Geospatial
  • Education
  • Unsure/Other (explain below)

• If you selected Unsure/Other, briefly explain:

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  • Creating a test suite
  • Enabling Continuous Integration
  • Adding a specific feature
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  • Other

• Explain briefly below if there's something specific you'd like help with:

• Any other questions or issues we should be aware of?:

P.S. Have feedback/comments about our review process? Leave a comment here

[eliotwrobson]

@adejumoridwan thanks for the help request! EiC here, just want to acknowledge that I've seen this request and start looking for someone that can help.

In the meantime, could you provide some context on what kind of help you would like with the package? This will help us get you assistance faster.

[adejumoridwan]

@eliotwrobson thank you very much. I would like to submit my package for review. I have set up some tests, but I would like to know if it is sufficient.
I have not set up continous integration though.

Also what are the things to be improved to consider my package for a review.

[eliotwrobson]

@adejumoridwan apologies for the delay, I think adding continuous integration that includes test coverage would definitely be a prerequisite for review. Handling a few other things for now but can make another pass later with more thorough comments.

[adejumoridwan]

@eliotwrobson Thanks very much.