People have been using data for hundreds of years. They collect, analyze, group, and visualize them in different formats so that the “story” behind the data is easier to transmit and understand. The ability to highlight the value and implicitly the usefulness of data collections (i.e. Data Analysis and Visualization) is one of the basic skills a good researcher or any professional working with data needs.
This helps to better understand the nature of a data set and ease the ability to communicate to an external (technical and non-technical) audience the results through an appropriate message. During the phases of data exploration and analysis it is very important to understand their nature, the details that become essential for the stage of visual representation. Python (www.python.org) is an excellent programming language for data exploration and analysis, especially thanks to the support of versatile libraries such as Numpy, Pandas, Matplotlib and many more.
Trainers: Bogdan GRECU & Natalia POIATA, National Institute for Earth Physics, Romania
Paintings on the wall of Lascau Cave depicting scenes from many thousand of years ago (left). Graphic maps and seismic waveforms generated based on or recorded by the RaspberryShake network of educational seismometers (right).
Who is the workshop for?
Students and young researchers in Geophysics, or other fields, interested in data processing and visualization, data management, disaster support systems based on automatically data processing
The purpose of the workshop:
● To familiarize the participants with the basics of Python programming language and
● To learn about Jupyter Notebook application
● To introduce the participants into the basics of data analysis and visualization using Python libraries
● Hands-on real seismological data (e.g. discovering and downloading waveforms, basic processing – filtering, correcting data, spectral analysis, earthquake catalogs).
Topics addressed in the workshop:
● Use of Jupyter Notebook
● Data analysis with Pandas
● Data visualization with Matplotlib
● ObsPy – a tool for processing seismological data
● Case study: data collections, earthquake detection and
location from continuous data
The Jupyter platform (https://jupyter.org/) provides an extremely useful tool (JupyterNotebook) that allows to create and run codes, analyze data, integrate content and share results. Formerly called IPython Notebook, the application facilitates collaborative work and proper documentation of codes, graphs or maps obtained. It is already a common tool used by researchers because it is user friendly and provides various formats for exporting and publishing results (PDF, HTML, ipynb, dashboards, slides, etc.).
