Getting Started

Getting Started#

What is GeoCAT Applications?#

GeoCAT Applications is a community resource managed by the GeoCAT team. Inspired by NCL Applications.

GeoCAT Applications is broken into two main sections:

  1. Applications

  2. NCL to Python

Applications#

Applications is designed to be a quick reference to demonstrate capabilities within the scientific Python ecosystem that may be relevant to your geoscience workflows

NCL to Python#

NCL to Python consists of pages that explain specifically how to achieve something that was possible in NCL in Python, including any algorithmic differences, guidance regarding replication under different conditions or circumstances, and any other relevant comparisons between the NCL and Python functionality

This is part of the GeoCAT team’s commitment to NCL and NSF NCAR’s Pivot to Python

These pages assume that the user has a working knowledge of NCL and are looking for transitional resources for specific functions. They also are not intended to be a comprehensive explanation of the Python recommendations, but rather a guide for users who are already familiar with the NCL function and are looking for “equivalent” Python code

New to Python?#

If you are new to Python or want to learn more, Project Pythia offers high-quality, geoscience-oriented Python tutorials

Pythia Foundations covers prerequisites that will be helpful to learn for GeoCAT Applications like:

  • Getting Started with Python

  • Getting Started with Jupyter

  • Working with NumPy and Pandas

  • Plotting with Matplotlib

New to Jupyter Notebooks?#

Jupyter Notebooks provide an interactive interface to write, execute, and visualize code. Traditionally, code is written in a script and executed in order from beginning to end each time a script is run. Instead, Jupyter Notebooks allow you to divide code into cells that can be executed individually and in any order. Each cell in a Jupyter Notebook can be filled with executable code, markdown, or raw code. Jupyter Notebooks have grown in popularity because they offer a simple method to include plain English description alongside code to improve readability. In addition, because each cell can be run in any order, it is possible to organize a notebook to avoid having to constantly re-run parts of a script that might take longer to run than others, like like retrieving data. The outputs of each cell appear below the cell without the need for typing print or plt.show().

In addition to Pythia Foundations “Getting Started with Jupyter” , you can see the Project Jupyter Documentation for more information. or try it out yourself online.

Each tutorial and resource page of GeoCAT Applications is built from Jupyter notebooks, however, on the GeoCAT Applications webpage, each page is a static resource. For information about how to download GeoCAT application to run locally, please see the Contributor Guide.

If you have any questions, please leave us a message on GeoCAT Applications Issues or in GeoCAT Applications Discussions. You can also reach us by email at geocat@ucar.edu.