The second part elaborates on the theme of data transformation and scientific programming by concentrating on regular expressions, various file formats used in a scientific context, how to parse and transform data, interact with databases and external programs. It also covers the libraries that are useful for scientific programming such as numpy, scipy, matplotlib and pandas.Hands-on sessions provide real world challenges with increasing levels of complexity.

Detailed time/place info

27/11/2017 - 09.00 - 13.00
30/11/2017 - 09.00 - 13.00