Python is an ever more popular language for doing data science. Python has strong support for research and data analysis through general tools like numpy, scipy and pandas (statistics) and more specialized packages like for instance astropy, biopython and obspy (seismology). Jupyter Notebooks (previously IPython Notebooks) provide a great tool for both doing interactive exploration of data, documenting experiments and analysis, and for sharing research with colleagues and the rest of the community.

This short-course will be a hands-on workshop (bring your laptop!) introducing the data science capabilities of Python and Jupyter. We will cover how to read data in different formats, tools for cleaning, analysing and plotting data, and how to take advantage of the Jupyter Notebook for documentating and sharing your work.

Previous experience with Python is not necessary, although some general understanding of programming will be very helpful. This course will not attempt to teach Python, but will provide examples and demonstrations that is a good starting point for you using Python and Jupyter in your own work.

Preparation:
Install Anaconda (https://www.continuum.io/downloads), 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.

All material for the short course will be made available at https://github.com/gahjelle/data-analysis-with-python