EGU 2017: Data analysis with Python and Jupyter

During the EGU 2017 we presented a short course introducing how to do data science with Python and Jupyter. This is the material used in the course. The course itself was 90 minutes. However, there is a bit more material that can also be used for self-study and for finding references that go more in-depth.

Preparation

Install Anaconda, Python 3.x version. Anaconda is an open data science platform which includes Python and most packages necessary for doing data science. Anaconda can be installed even without root/administrator privileges.

Material

The course is made available as a series of Jupyter Notebooks. The notebooks can be read directly here at Github, but you will have a better, more interactive experience by downloading them and running the locally. How to do this is explained in Notebook 2: Jupyter Notebooks.

This short course is not a course in Python, the programming language. Instead we aim to show you how Python has become a full-blown platform for doing data science.

The following short lessons are available:

• Reading files
• Working with JSON-data
• Numerical data in numpy
• Pandas and time series
• Plotting data
• Storing data
• Distributing Jupyter notebooks