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.

We will learn:

how to identify some of the most common data formats (raster formats) in environmental Sciences i.e. netCDF and HDF (HDF-EOS and HDF5), GeoTIFF.

How to view the content of these binary files

How to identify the provenance and explore metadata

How to organise your data and develop a simple data management plan to ease your work

How to access and process data in commonly used raster formats such as GeoTIFF, HDF-EOS, HDF5 and netCDF.

How to combine them with vector datasets such as ESRI Shapefile and GeoJSON.

The meaning of these terms will become clear as we work through the python notebooks.

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.
Learners need to have some prior knowledge of Python. For instance, what is covered in the Software Carpentry lesson Programming with Python is more than sufficient.
Learners must install Python and a few additional python libraries before the class starts. See the setup instructions
Learners must get the metos data before class starts: please download and unzip the file metos-python-data.tar.

Please see the setup instructions for details.

Schedule

	Setup	Download files and install packages required for the lesson
00:00	1. Introduction	Where to start? Why using common data formats?
00:00	2. Data Formats in Environmental Sciences	What are the most common data formats in Environmental Sciences? raster vs vector formats? What are the most common python packages to read/write netCDF, HDF, GeoTIFF data files?
00:00	3. Intro to Coordinate Reference Systems & Spatial Projections	What are Coordinate Reference Systems?
00:00	4. Plotting spatio-temporal data with Python	How can I create maps with python?
00:00	5. Data analysis with python	What is SciPy? How can I use Scipy?
00:00	6. Visualize and Publish with Python	How to create animation plots and publish them on the web?
00:00	7. Handling very large files in Python	How to manipulate large netCDF or HDF files? How to optimize my workflow? What are xarray and dask?
00:00	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.