Course page for

Applied Scientific Data Handling

(with Python) NAKE014

This is the course -page for the course NAKE014.

Course Preparation:

The course will be given in a computer room at the Chemistry Center. There are 12 computer and 24 places available. The usage of Laptops is possible and highly recommended. As preparation please ensure that a version of Python 2.7 (not 3.x !!!) is installed. Python is based on a large number of modules that significantly enhance its capabilities. To effectively work with data a few of those packages are very useful. Please find below some instruction how to create the necessary environment on your computer.

One key idea in this course is to achieve sufficient knowledge to work with data from your field of work. Please try to prepare a small dataset in the ASCII (plain text) format that represents a typical problem in your field. e.g. one matrix with time-spectrum, one dataset with many samples taken under a variety of parameter, a scan from any device/beamline... In order to accommodate such a wide spectrum of possibilities it will be necessary to have plain text (structured data that can be viewed with a program like Notepad on windows).

We will provide all necessary material during the course. There is an endless number of books to which we have access in the university. Each has a different approach and the choice is very individual. This literature is just a selection for further reading and specific questions. (all are digitally available at the moment)

Python Installation:

Windows user (all versions): To avoid installing all the packages step by step I would recommend to use one of the freely available pre-packaged distributions which contains all the necessary modules of this course. e.g. or (If you don't know, install anaconda)

In addition I highly recommend to use either an advanced text editor or a specialized IDE (integrated development Environment). We will look on Spyder and Jupyter which are installed in these packages. But is good to have a better editor available then the normal notepad. For Windows I would recommend notepad++

Linux and Mac user: Depending on your distribution you have either a package handler or the “port” function (for mac). Please make sure that you have the following packages installed: ipython, sys, os, pandas, scipy, numpy, matplotlib, scikit-learn, seaborn, jupyter, spyder, lmfit

course schedule 2017

Schedule as image, date 15th November 2017

Google Drive with Files: (removed until next round)

Recommended Literature (Digitally available):


Statistics and general Python:

Sequence alignment Book