https://annefou.github.io/metos_python/

Python for analyzing and visualizing spatio-temporal data
https://annefou.github.io/metos_python/

Last synced: about 2 months ago
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Python for analyzing and visualizing spatio-temporal data

• Host: GitHub
• URL: https://annefou.github.io/metos_python/
• Owner: annefou
• License: other
• Created: 2017-07-04T06:48:20.000Z (over 7 years ago)
• Default Branch: gh-pages
• Last Pushed: 2019-05-17T12:20:20.000Z (over 5 years ago)
• Last Synced: 2024-08-01T20:38:18.722Z (5 months ago)
• Language: Jupyter Notebook
• Homepage: https://annefou.github.io/metos_python/
• Size: 51.4 MB
• Stars: 25
• Watchers: 5
• Forks: 11
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md
  • Citation: CITATION
  • Authors: AUTHORS

Awesome Lists containing this project

• awesome-earthobservation - Working with Spatio-temporal data in Python - With Software Carpentry lessons and Data Carpentry lessons you learn the fundamental data skills needed to conduct research in your field and learn to write simple programs. This one-day workshop will introduce you to Python for analyzing and visualizing spatial-temporal data. We will be using datasets from the environmental sciences that are freely available. (Software and saas / Jupyter based training resources)

README

        
# Python for analyzing and visualizing spatio-temporal data

These lessons will introduce you to Python for analyzing and visualizing spatio-temporal data. 

We are using datasets from the environmental sciences that are freely available.

Please visit [https://annefou.github.io/metos_python/](https://annefou.github.io/metos_python/) for the lesson web page.

[![DOI](https://zenodo.org/badge/96184802.svg)](https://zenodo.org/badge/latestdoi/96184802)

These lessons have been developed at the University of Oslo by **Ana Costa Conrado**, **Gladys Nalvarte** and **Anne Fouilloux**.

Who: The course is aimed at graduate students and other researchers. 

Prerequisites:

Learners need to understand what files and directories are and what a working directory is. These concepts are covered in the [Unix Shell lesson](http://swcarpentry.github.io/shell-novice/).

Learners need to have some prior knowledge of Python. For instance, what is covered in the Software Carpentry lesson [Programming with Python](http://swcarpentry.github.io/python-novice-inflammation/) is sufficient.

Learners must install Python. See the [setup instructions](https://annefou.github.io/metos_python/setup/).

A few additional python libraries need to be installed before the class starts. See [here](https://annefou.github.io/metos_python/setup/) which packages and how to install them.

Learners must get the metos data before class starts: please download and unzip the file [metos-python-data.tar](https://zenodo.org/record/995709/files/metos-python-data.tar).