Skip to content
Switch branches/tags
Go to file

Latest commit


Git stats


Failed to load latest commit information.

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


Packages and Tutorials



Reading self describing file

General Python resources

Free online Tutorials


No description, website, or topics provided.



No releases published


No packages published