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README.md

Python for Earth Sciences

Instructor: Rebekah Esmaili

Contributors: Kriti Bhargava and Eviatar Bach


A crash course in Python focusing on reading and visualizing data-sets used in Earth sciences.

This code is interactive! Click: Binder


Getting Started

This workshop will cover:

  • Launching Jupyter Notebooks
  • Working with arrays using the Numpy package
  • Importing text datasets using the Pandas package
  • Creating simple graphics with Matplotlib
  • Importing scientific data formats, such as netCDF and GRIB2
  • Creating maps from datasets

Installation requirements

"I am really new to Python!"

  • I recommend launching binder, which is a "cloud version" of this course. No installation required! Binder

  • Need help with Binder? Video tutorial on YouTube.

"I have used Python before!"

  • If you wish to run the examples locally, I recommend installing Anaconda. If you are having trouble with your installation, contact the instructor before the course or use binder.
  • Need help installing Anaconda? Video tutorial on YouTube.
  • Download the contents of the GitHub repository to your computer.
  • Launch Jupyter Notebooks from the Anaconda Navigator. This will open a window in your default browser. Navigate to the folder that contains the notebooks (*.ipynb) and click on the tutorial for the day.
  • New to Jupyter? Here's a video tutorial on YouTube.
  • Additional packages:
    • Launch the Anaconda Prompt (Windows) or Terminal (MacOS/Linux). Then copy/paste and hit enter:
      conda install -c conda-forge cartopy
      conda install -c conda-forge netCDF4
      conda install -c conda-forge pygrib
      
    • If there are no errors, then you are set-up!
    • Alternatively, if you are familiar with environments, you can use the environments.yml to install the necessary packages.

I do not recommend:

  • Using Python on a remote server for this tutorial (I cannot help troubleshoot)
  • Using your operating system's Python or a shared Python installations unless you are advanced!

Course Philosophy

  • Increase accessibility of satellite data and analysis
  • Teach Python using practical examples and real-world datasets
  • Promote reproducible and transparent scientific research

Resources

Packages and Tutorials

Pandas


Matplotlib


Reading self describing file


General Python resources

Free online Tutorials

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