https://github.com/martibosch/swiss-urbanization-post

Materials to reproduce the blog post of https://martibosch.github.io/managing-analysis-workflows-geodata-make/
https://github.com/martibosch/swiss-urbanization-post

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Materials to reproduce the blog post of https://martibosch.github.io/managing-analysis-workflows-geodata-make/

• Host: GitHub
• URL: https://github.com/martibosch/swiss-urbanization-post
• Owner: martibosch
• License: gpl-3.0
• Created: 2019-02-21T15:57:48.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2019-02-26T09:59:59.000Z (almost 6 years ago)
• Last Synced: 2024-06-11T16:31:31.899Z (7 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 207 KB
• Stars: 1
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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swiss-urbanization-post

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Materials to reproduce the blog post of http://martibosch.github.io/managing-analysis-workflows-geodata-make/

Prerequisites: a Python distribution with conda

Instructions to reproduce (commands executed from the root directory of this repository):

1. Create the conda environment by executing `make create_environment`

2. Activate the environment by executing `conda activate swiss-urbanization-post`

3. Update the `src/data/download_clc.py` script so that it downloads the [CORINE Land Cover](https://land.copernicus.eu/pan-european/corine-land-cover) datasets for the years 2000, 2006 and 2012 (the datasets are open but require registration) to the `data/raw/clc` directory, **or** contact me in order to get a temporary access keys to a S3 service that will provide you such files without need to change the code.

4. Generate the figure to `reports/figures/swiss-urbanization.png` by executing `make figure`

See the [overview](https://github.com/martibosch/swiss-urbanization-post/blob/master/notebooks/overview.ipynb) notebook for a more visual description of the workflow.

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Project based on the cookiecutter data science project template. #cookiecutterdatascience