Open data project on exploration of healthcare data for the ASEAN region, currently focusing on Malaria and Dengue.
Social Coding board: https://github.com/DataKind-SG/healthcare_ASEAN/projects/1
Slack Channel on DataKindSG (datakindsg.slack.com) team: #healthcare_asean
The data folder has been uploaded to the github repo data\ folder.
Further information: docs\README.md
- weekly data
- location: state/province level
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── docs <- A default Sphinx project; see sphinx-doc.org for details
│
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
│ │
│ ├── data
│ │ ├── download <- Scripts for downloading from each raw data source
│ │ │ └── logconf.ini <- setup for logging configuration for scripts in download/
│ │ ├── download.py <- Script to download raw data using modules in `download/`
│ │ │
│ │ ├── clean <- Scripts to clean raw data
│ │ ├── clean.py <- Script to clean raw data using modules in 'clean/'
│ │ │
│ │ └── logconf.ini <- setup for logging configuration for scripts in data/
│ │
│ ├── features <- Scripts to turn raw data into features for modeling
│ │ └── build_features.py
│ │
│ ├── models <- Scripts to train models and then use trained models to make
│ │ │ predictions
│ │ ├── predict_model.py
│ │ └── train_model.py
│ │
│ └── visualization <- Scripts to create exploratory and results oriented visualizations
│ └── visualize.py
├── test <- Directory for souce codes testing
│ ├── func <- Directory for souce codes functional testing
│ │ ├── data
│ │ ├── features
│ │ └── models
│ ├── unit <- Directory for souce codes unit testing
│ │ ├── data
│ │ ├── features
│ │ └── models
└── tox.ini <- tox file with settings for running tox; see tox.testrun.org