exploartive Analyse der vom BAG veröffentlichten Kennzahlen zu den Schweizer Spitäler. Die Kennzahlen sind auf opendata.swiss verfügbar.
- clone the repository
- install the environment
make create_environment. - Activate the environment. If using conda:
source activate kennzahlen_schweizer_spitaeler - install the required packages
make requirements
the data is downloaded from opendata.swiss to the data/raw directory. Just type make download_data.
├── 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.
│
├── 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`.
│
├── 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 <- Scripts to download or generate data
│ └── make_dataset.py
│
└── visualization <- Scripts to create exploratory and results oriented visualizations
└── visualize.py
Project based on the cookiecutter data science project template. #cookiecutterdatascience