Python is a high-level programming language designed to be easy to read and write, using simple, English-like syntax that lets beginners express ideas without getting lost in punctuation and boilerplate. It runs on many platforms, has a large standard library that provides ready-made tools for common tasks, and benefits from a huge community that shares tutorials, modules, and solutions.
You write Python as a sequence of statements that perform operations such as computing values, controlling flow with conditionals and loops, and manipulating text and files. Python programs use variables to hold data and built-in data types like numbers, strings, lists, and dictionaries to organise information in ways that match how you think about problems.
One of Python’s most important features is functions: named blocks of code that take inputs, perform a defined task, and return results. Functions let you break a program into smaller, reusable pieces, hide complexity, test units of work independently, and document intent with a clear name so programs are easier to maintain and share.
Python is widely used in data analysis because libraries such as pandas, NumPy, and Matplotlib let you read and clean data, perform numerical and statistical operations, and create visualisations with concise code. Analysts write functions to encapsulate cleaning steps, reusable transforms, and model-evaluation procedures so workflows are reproducible, easier to debug, and simple to run again when new data becomes available.
I highly recommend DataCamp for learning Python.