# Python & Programming

> Hands-on Python tutorials — the language, its standard library and the data stack that every analytics and ML job assumes you already know.

- [Programming for Data Science: How Much Code Do You Really Need?](https://www.1stepgrow.com/articles/programming-for-data-science/) — Programming for data science: how much SQL and Python you need, what reproducible code looks like, the notebook traps, and where AI assistants help or hurt.
- [The Future of Programming Languages: What Is Actually Changing](https://www.1stepgrow.com/articles/future-of-programming-languages/) — The future of programming languages, using TIOBE, Stack Overflow and GitHub data: why Python and TypeScript lead, types are winning, and what to learn.
- [NumPy Tutorial for Beginners: NumPy Arrays in Python (Part 1)](https://www.1stepgrow.com/articles/numpy-tutorial/) — NumPy tutorial for beginners: what an array is, why it ran about 20 times faster than a list here, how one stray string turns numbers into text, and more.
- [NumPy Indexing and Slicing: Views, Masks and Fancy Indexing (Part 2)](https://www.1stepgrow.com/articles/numpy-indexing-slicing/) — NumPy indexing and slicing explained: why editing a slice changes your original array, when masks and fancy indexing copy instead, and how to avoid both bugs.
- [NumPy Broadcasting in Python: Rules and Common Bugs (Part 3)](https://www.1stepgrow.com/articles/numpy-broadcasting/) — NumPy broadcasting explained: the two shape rules, why a (3,1) and a (4,) array give (3,4), and the silent bug that turns a vector sum into a matrix.
- [NumPy Aggregation, Sorting and Linear Algebra in Python (Part 4)](https://www.1stepgrow.com/articles/numpy-aggregation-functions/) — NumPy aggregation along axes, NaN-safe statistics, argmax, sorting and linalg.solve, plus why NumPy and pandas return different standard deviations.
- [Plotly Tutorial for Python: Basic Interactive Charts (Plotly Part 1)](https://www.1stepgrow.com/articles/plotly-tutorial/) — Plotly tutorial for Python: interactive charts in one Plotly Express call, when to use Graph Objects, styling, faceting, and HTML exports 100x smaller.
- [Advanced Plotly Charts: Subplots, Animation and 3D (Plotly Part 2)](https://www.1stepgrow.com/articles/advanced-plotly-charts/) — Advanced Plotly charts in Python: subplots, dual axes, animation, 3D and heatmaps, plus the axis-range mistake that silently drops points from animations.
- [Advanced Matplotlib Styling and Customisation in Python (Part 5)](https://www.1stepgrow.com/articles/matplotlib-styling-customization/) — Matplotlib styling for report-ready charts: rcParams, style sheets, colormaps, annotation and clean export, and why plt.style.use('seaborn') now fails.
- [Python Classes and Objects: Object-Oriented Programming, Part 1](https://www.1stepgrow.com/articles/python-classes-objects/) — Python classes and objects explained with tested code: __init__, self, dunder methods, properties and dataclasses, plus the shared-list bug to learn first.
- [Inheritance and Composition in Python: OOP in Python, Part 2](https://www.1stepgrow.com/articles/python-inheritance-composition/) — Inheritance and composition in Python with tested code: when to use each, how super() really works, duck typing, and why deep class hierarchies backfire.
- [Python Tuples: Unpacking, Dict Keys and the Trailing-Comma Trap](https://www.1stepgrow.com/articles/python-tuples/) — How to use Python tuples well: creating them, unpacking, using them as dict keys, named tuples, and the one-element and += gotchas that catch everybody.
- [Lists vs Tuples in Python: Differences and When to Use Each](https://www.1stepgrow.com/articles/lists-vs-tuples-python/) — Lists vs tuples in Python beyond 'one is mutable': the real differences in hashability, memory, safety and intent, plus a decision rule that works in practice.
- [Python Strings: F-Strings, Methods and the strip() Trap](https://www.1stepgrow.com/articles/python-strings/) — Python strings in practice: f-strings, slicing, the methods worth memorising, why += loops slow down, and the encoding default that breaks scripts on Windows.
- [Regular Expressions in Python, Part 1: Syntax, Functions, Flags](https://www.1stepgrow.com/articles/regular-expressions-in-python/) — Regular expressions in Python from the ground up: raw strings, core syntax, match vs search vs fullmatch, flags, and five mistakes that silently break patterns.
- [Advanced Python Regex: Groups, Lookarounds and Substitution (Part 2)](https://www.1stepgrow.com/articles/advanced-python-regex/) — Advanced Python regex with tested output: named groups, lookarounds, re.sub with a function, and why a 24-character input made (a+)+$ run for 10 seconds.
- [Exception Handling in Python: Catch Narrowly, Log Everything](https://www.1stepgrow.com/articles/python-exception-handling/) — Exception handling in Python done properly: try, except, else and finally, custom exceptions, chaining and logging, and why a bare except can break Ctrl-C.
- [Iterators and Generators in Python: Process Files Larger Than RAM](https://www.1stepgrow.com/articles/python-iterators-generators/) — Iterators and generators in Python explained: yield, pipelines that stream big files in flat memory, itertools, and why a generator silently runs only once.
- [Python Lambda Function: Where It Helps and When to Use def](https://www.1stepgrow.com/articles/python-lambda-functions/) — A Python lambda function is a one-expression anonymous function. Learn where it helps (sort keys, callbacks), when def wins, and the loop bug it causes.
- [Python Operators: What Each One Returns, and Where It Bites](https://www.1stepgrow.com/articles/python-operators/) — Python operators explained with outputs for every example, plus why is works for 256 but fails for 257 and why and/or rarely return booleans.
- [Python Numeric Data Types: int, float, Decimal and When to Use Each](https://www.1stepgrow.com/articles/python-numeric-data-types/) — Python numeric data types explained: int, float, Decimal, Fraction and complex, why 0.1 + 0.2 is not 0.3, and how to handle money without rounding errors.
- [Python Functions: Writing User-Defined Functions Worth Reusing](https://www.1stepgrow.com/articles/python-functions/) — How to write Python functions: arguments, defaults, *args and **kwargs, scope, type hints and docstrings, plus the mutable default bug everyone hits once.
- [Python Basics: Names, Collections, Control Flow and Comprehensions](https://www.1stepgrow.com/articles/python-basics/) — Python basics with runnable examples: names and objects, lists, dicts and sets, control flow and comprehensions, plus the traps behind most beginner bugs.
- [How to Install Anaconda on Windows: Python and Jupyter Notebook Setup](https://www.1stepgrow.com/articles/install-anaconda-windows/) — How to install Anaconda on Windows step by step: which PATH checkbox to leave unticked, licence terms, a Jupyter kernel, and fixes for common conda errors.
- [How to Install Anaconda on Mac: Python and Jupyter Notebook Setup](https://www.1stepgrow.com/articles/install-anaconda-mac/) — How to install Anaconda on Mac: the right Apple Silicon installer, the zsh fix for 'conda: command not found', licence terms, and a working Jupyter kernel.
- [Git and GitHub Tutorial: Install Git and Push to a Remote Repository](https://www.1stepgrow.com/articles/git-and-github-tutorial/) — A Git and GitHub tutorial for beginners: install Git, sign in with SSH or a token (GitHub rejects passwords), write .gitignore, push, and undo mistakes.