Python for Data Science#
This is a tutorial on Data Science with Python. This immediately raises the question: What is Data Science? The term has become ubiquitous, but there is no single definition. Some even consider the term superfluous, because what science does not have to do with data? Nevertheless, it seems to me that data science is more than just hype: scientific data has become increasingly voluminous and often can no longer be adequately tapped with conventional mathematical and statistical methods alone – additional hacking skills are needed. However, it is not a new field of knowledge that you need to learn, but a set of skills that you can apply in your field. Whether you are analysing astronomical objects, analysing machines, forecasting stock prices or working with data in other fields, the goal of this tutorial is to enable you to solve tasks programmatically in your field.
This tutorial is not intended to be an introduction to Python or programming in general; for that there is the Python basics tutorial. Instead, it is intended to show the Python data science stack – libraries such as IPython, NumPy, pandas, Matplotlib and related tools – so that you can subsequently effectively analyse and visualise your data.