Intro to Programming and Data Analytics with Python
Programming, or coding, is the construction of a set of repeatable instructions that tell a computer what to do. Usually this is in a text file of some kind which is then passed to a computer and 'run' or 'executed' using some other program. As we'll see, there are more and less sophisticated versions of this picture.
Programming is key to modern data analytics. Programming gives you:
- the chance to re-run analyses without having to push a series of buttons and menus each time.
- the chance to re-run analyses with variations; for example, on a series of files.
- the chance to build analyses which aren't in standard software available 'out of the box'.
- the chance to build analyses into workflows or interfaces for non-experts.
In this session, we'll look at building up analyses using the language Python. Python is a "scripting language": scripting languages are designed to do simple jobs as easily as possible. On the plus side they are:
- easy to learn;
- well supported by communities developing add-on 'libraries' of code that do specialist jobs.
On the downside, compared with languages like C++, Fortran, or Java, they tend to:
- run a little slower;
- be less orientated to building windows applications;
- be easier to write poor code in.
In short, they are perfect for data analysis, but less good for building full desktop applications or critical control systems with.
Work through the pages below to get an intro to Python with a data analysis case study. Instructions are in bold like this paragraph.