Introduction to Data Science ¶

This is an Introduction to Data Science. In ten lectures we overview and demonstrate a set of basic skills that everyone needs in order to visualize data and perform some fundamental data analysis. The idea of this handbook is to demonstrate how, with a little bit of Python programming, from a conveniently represented data you can get a new quality -- information. This handbook is written in Jupyter, which is an interactive environment ideal for experimenting with snippets of Python code.

Although our programming language of choice is Python, this handbook is not meant to teach Python programming. The goal of this hanbook is to demonstrate basic skills needed for data visualisation and data analysis, while the programming language is just a tool that makes it possible for us to formulate out ideas precisely and apply them on concrete examples. Python is a modern programming language that is constantly being upgraded and regularly maintained, and which is free to use. That makes it a convenient choice.

• 0. Running Jupyter notebooks
• 1. Introduction to Jupyter
• 2. Sequences of data and line charts
• 3. Bar charts and colors
• 4. The average and the median of a sequence of numbers
• 5. Frequency analysis and pie charts
• 6. Representing data as tables
• 7. Indexing and transposing a table
• 8. Modifying tables and writing to files
• 9. Sorting, filtering and frequency analysis
• 10. Jupyter and Excel