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The examples in this space should give you a good starting point how you can work with ECMWF services and data through Python using Jupyter notebooks.
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*[Visualisation meteorological data](visualisation) using ECMWF's [Magics](https://software.ecmwf.int/magics) plotting package for meteorological data.
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*[Retrieving and processing meteorological data](processing) using [Metview](https://software.ecmwf.int/metview) and related Python packages
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*[Download images and reproducing ECMWF Open Charts](opencharts) using new ECMWF Python libraries
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Many notebooks that showcase processing of ECMWF data using [Metview](https://metview.readthedocs.io/en/latest/) can now be found in Metview documentation page:
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*[Gallery of Jupyter notebooks](https://metview.readthedocs.io/en/latest/notebook_gallery.html)
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*[Gallery of small Python examples](https://metview.readthedocs.io/en/latest/gen_files/gallery/index.html)
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Each notebook has a list of nececary libraries needed for it to work and code to install it.
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If you clone this repo and want to explore all the notebooks. you can use the environment.yml file to create a conda environment and install all the libraries inside, using this command:
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If you clone this repo and want to explore all the notebooks, you can use the environment.yml file to create a conda environment and install all the libraries inside, using this command:
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`conda env create -f environment.yml`
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Note: All the libraries are frozen on 30th March 2023.
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Note: All the libraries are frozen on 09th January 2025.
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