Getting started with Python for planetary science


The Python visualization landscape could be intimidating for new users, due to the amount of different packages aimed to different users and scope.
We will briefly cover the different existing possibilities and focus on HoloViews , “an open-source Python library designed to make data analysis and visualization seamless and simple. With HoloViews, you can usually express what you want to do in very few lines of code, letting you focus on what you are trying to explore and convey, not on the process of plotting.” (from the official website).
I will show how to download an open dataset from Natural Earth, manipulate and interactively show it, visualizing great amount of data on a laptop.
Depending on the participating users skills, we can go on to show basic data exploration techniques, Python Data Analysis Library (pandas), machine learning in Python (scikit-learn).
If you ask, I’ll answer.


  • HoloViews is part of the PyViz, an open platform for helping users decide on the best open-source (OSS) Python data visualization tools for their purposes, with links, overviews, comparisons, and examples.
  • PyViz website shows how to use HoloViews together with other libraries to solve complex problems, including detailed tutorials and examples.
  • scikit-learn : Machine Learning in Python. Simple and efficient tools for data mining and data analysis. Accessible to everybody, and reusable in various contexts. Built on NumPy, SciPy, and matplotlib. Open source, commercially usable - BSD license.
  • pandas : the Python Data Analysis Library is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. pandas is a NumFOCUS sponsored project. This will help ensure the success of development of pandas as a world-class open-source project, and makes it possible to donate to the project.
  • Inspired from Jake VanderPlas’ great talk at at PyCon 2017 , The Python Visualization Landscape.
1 Like