Python Hydrosoc Workshop 2018¶
The volume of data collected and available to scientists has grown in magnitudes over the past decades. It has grown to an extent that cannot be effectively handled by spreadsheets passed from one person to another. Fortunately, the toolsets to handle large amounts of data have grown as well, although it can be quite hard to keep up with the rapid developments of these toolsets.
The Python programming language is one of the most popular languages for both general purposes and scientific. This is due in part by the ease of use, open source code, and the large open source community that has developed a number of professional level toolsets for a wide range of applications.
The general goal of this workshop is to teach Python tools specifically beneficial for natural/environmental scientists in New Zealand handling large amounts of data. This will be accomplished through a combination of practical exercises and presentations.
The intended audience for the workshop are people with very little to some experience with programming (Python or otherwise). Those people with a lot of Python programming experience will not likely get much out of the workshop unless they have not used the Pandas package in the past.
The workshop will cover the fundamental handling of tabular data and the associated processing and analysis tools. We will be primarily using the toolset contained within the Pandas package. This will include reading/writing data, indexing, reshaping, computations, joining tables, time series handling, and visualization.
The main prerequisite for the workshop is the Introduction to Python course by the Monash University. The links provided by each chapter can be run independently without the installation of Python on your PC. Please go through at least the first 5 chapters before coming to the workshop. The last two are optional but recommended.
Please contact the instructors via the email addresses below to sign up for the workshop. There will be a maximum of 30 attendees for the workshop. Suggestions for advanced topics or examples are welcome.