Learning a new language
What exactly is programming and how do we get started?
Programming is a type of written language that allows us to send instructions to devices and computers to complete specific tasks, without being ambiguous. Each language has its own set of rules or ‘synax’, making each unique in its own way.
One of the most widely used programming languages for data science is Python, which was developed in 1991 by a Dutch programmer named Guido van Rossum. It is widely used in the data science field due to its versatility, its simplicity (compared to other programming languages) and the vast amount of compatible analysis packages that can be used with it. It is one of the top three most popular programming languages according to the well-known TIOBE index.
When we are writing Python code, we write it in a high-level language that we can easily read and understand. When you run your program, Python will then analyse your code, line by line, and attempt to ‘translate’ or ‘interpret’ your high-level language into a low-level language, which is easier for your computer/device to understand.
However, we need a medium to be able to actually use, write and run our Python code. We could just use the bog-standard Python editor but we also need to make sure it is suitable for our needs in the data science field. An excellent example of this is Jupyter Notebook, which is an open-source application that gives us the ability to neatly organise and narrate our code in a format recognised and used by institutions around the world, such as Google, Microsoft and NASA.
Using Jupyter Notebook allows us perform repetitive calculations with different variations very quickly due to its efficient workflow. We can load entire data sets and even display useful graphs based on our data, all with just a few lines of code.
As we will be using Python and Jupyter Notebook throughout this course, we’ve included a help guide to get you started. This is available in the downloads area.
Download, open and read through the Jupyter Notebook Help guide to get you up and running.
Download the Jupyter cheat sheet zip file which shows you all the different ways in which you can display cells in Python Notebooks. Extract the zip file and upload its contents into your Jupyter Notebook. If you’re not sure how to extract a zip file, see the WikiHow site for guidance.
At the end of the cheat sheet there’s a task to help you get to grips with the basics. Complete the task within your Jupyter Notebook.
WikiHow. (2020, January 26). How to unzip a file. https://www.wikihow.com/Unzip-a-File
TIOBE. (2020). TIOBE Index for July 2020. https://www.tiobe.com/tiobe-index/
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