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netcdf_in_python_from_beginner_to_pro

https://github.com/nordatanet/netcdf_in_python_from_beginner_to_pro

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 5 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
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    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (6.5%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: NorDataNet
  • License: gpl-3.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 8.26 MB
Statistics
  • Stars: 5
  • Watchers: 1
  • Forks: 2
  • Open Issues: 0
  • Releases: 1
Created over 2 years ago · Last pushed 11 months ago
Metadata Files
Readme License Citation

README.md

NetCDF in Python: From beginner to pro

Want to learn how to work with NetCDF files? Know a bit of Python? You have come to the right place!

This course has been designed to help you understand NetCDF files, get data out of them and create your own NetCDF files. The course is suitable for beginners who know nothing about NetCDF files and those who are new to Python. However, more experienced users should also be able to learn a lot from this course.

You may be here because you are interested in publishing FAIR data. Did you know that a NetCDF file is not necessarily FAIR unless it adheres to certain conventions? You will learn about the Climate and Forecast (CF) conventions (https://cfconventions.org/) and the Attribute Convention for Data Discovery (ACDD - https://wiki.esipfed.org/AttributeConventionforDataDiscovery_1-3), and how to make sure your files are compliant with them.

You can view the Jupyter book at https://nordatanet.github.io/NetCDFinPythonfrombeginnertopro

How to cite this course

If you think this course contributed to the work you are doing, consider citing it in your list of references. Here is a recommended citation:

Marsden, L. (2024, April 19). NetCDF in Python - from beginner to pro. Zenodo. https://doi.org/10.5281/zenodo.10997447

And you can navigate to the publication and export the citation in different styles and formats by clicking the icon below.

DOI

Owner

  • Name: Norwegian Scientific Data Network
  • Login: NorDataNet
  • Kind: organization
  • Email: nordatanet@met.no

Common software repository for the Norwegian Scientific Data Network infrastructure.

Citation (CITATION.cff) 

abstract: '<p>This course has been designed to help you understand NetCDF files, get
  data out of them and create your own NetCDF files. The course is suitable for beginners
  who know nothing about NetCDF files and those who are new to Python. However, more
  experienced users should also be able to learn a lot from this course.</p>

  <p>You may be here because you are interested in publishing FAIR data. Did you know
  that a NetCDF file is not necessarily FAIR unless it adheres to certain conventions?
  You will learn about the Climate and Forecast (CF) conventions (https://cfconventions.org/)
  and the Attribute Convention for Data Discovery (ACDD - https://wiki.esipfed.org/Attribute_Convention_for_Data_Discovery_1-3),
  and how to make sure your files are compliant with them.</p>'
authors:
- affiliation: Norwegian Meteorological Institute
  family-names: Marsden
  given-names: Luke
  orcid: 0000-0002-9746-544X
cff-version: 1.2.0
date-released: '2024-04-19'
doi: 10.5281/zenodo.10997447
license:
- cc-by-4.0
title: NetCDF in Python - from beginner to pro
version: v1.0.0

GitHub Events

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  • Issues event: 1
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Last synced: 7 months ago

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  • Total issues: 1
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  • Issues: 1
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  • Average time to close issues: 35 minutes
  • Average time to close pull requests: N/A
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  • Average comments per pull request: 0
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Dependencies

requirements.txt pypi
  • jupyter-book *
  • matplotlib *
  • numpy *
  • xarray *