101 Polars Exercises for Data Analysis (with Solutions)
Master Polars with 101 hands-on exercises and solutions, covering DataFrames, groupby, joins, window functions, lazy eval, and more.
Python
Python tutorials from Machine Learning Plus: hands-on guides with worked examples and code you can read, copy and run. Start with the fundamentals and work through to the applied posts in the Python track.
2026 3
101 Pandas Exercises for Data Analysis (Interactive)
101 interactive pandas exercises with solutions. Edit and run every code block directly in your browser, no installation needed.
Build Your First AI App with Python, Step-by-Step Tutorial
Build your first AI app with Python and the OpenAI API. Step-by-step tutorial covering chat completions, streaming, error handling, and cost control...
2025 9
Why Python Lacks Traditional OOP Encapsulation
Unlike Java Python treats encapsulation as a guideline, not a rule. Understand how this philosophy shapes OOP practices.
Memory Optimization in Python: How slots Works
Understand __slots__ in Python, a technique that replaces dynamic dictionaries with fixed attributes for faster, more efficient classes.
Understanding Python Descriptors and the __set_name__ Method
Learn how Python descriptors work with __set_name__. Control attribute access and understand descriptor protocols with clear examples.
Python’s Magic Methods: How to Overload Operators Properly
Discover how operator overloading is implemented using magic methods, allowing custom classes to integrate with Python's core operations.
Python @property: Getters, Setters, and Attribute Control Guide
Learn to use Python's @property decorator to implement getters and setters for safe attribute access and data validation in OOP.
Python Method Decorators- @classmethod vs @staticmethod vs @property
Understand Python's key method decorators: when to use @classmethod for class state, @staticmethod for pure functions, and @property for attribute...
Python ABCs- The Complete Guide to Abstract Base Classes
Explore Python's abc module, learn how Abstract Base Classes enforce interfaces, create robust hierarchies, and improve your OOP design.
Inheritance vs. Composition in Python- When to Use Which
Master Python's inheritance and composition, how they work, when to use each, with clear examples. Elevate your OOP skills effectively.
How Python Handles Multiple Inheritance- MRO Explained
Learn to design robust Python class hierarchies by mastering multiple inheritance and Method Resolution Order (MRO) behavior.
2024 1
Python Exercises – Level 1
Python exercises to practice as a beginner. These are devised as mini tasks that you might need to apply when programming with Python.
2023 10
How to convert Python code to Cython (and speed up 100x)?
Using Cython, you can speed up existing Python code by an order of 100x or more. This is possible because Cython converts some of the Python code to...
How to convert Python to Cython inside Jupyter Notebooks?
Lets see how to convert Python to Cython inside Jupyter Notebooks?
Install opencv python – A Comprehensive Guide to Installing “OpenCV-Python”
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV-Python is a Python...
Scrapy vs. Beautiful Soup: Which is better for web scraping?
Web scraping is the technique of extracting data from a specific website or web page. Let's understand how to use Scrapy for web scraping of Reddit...
install pip mac – How to install pip in MacOS?: A Comprehensive Guide
Pip is a widely used package manager for Python, allowing you to install and manage Python packages easily. In this blog post, we'll explore various...
add Python to PATH – How to add Python to the PATH environment variable in Windows?
Adding Python to the PATH environment variable in Windows allows you to run Python commands from any directory within the command prompt
Numpy.random.randint() in python
Numpy.random.randint is used to get random integers from low to high values. The low value is included while the high value is excluded while...
How to use numpy.random.uniform() in python.
The numpy.random.uniform() function is used to create an array with random samples from a uniform probability distribution of given low and high...
Numpy.sort() in python
The numpy.sort() function in python is used to sort the array along a specified axis.
numpy.median() – How to compute median in Python
numpy.median function is used to calculate the median of an array along a specific axis or multiple axes
2022 6
How to deal with Big Data in Python for ML Projects (100+ GB)?
The size of the data you can load and train in your local computer is typically limited by the memory in your computer. Let's see how to deal with...
Python Module – What are modules and packages in python?
Any Python files is a Module in Python. A python package is a collection of such modules along with a `__init__.py` file. Let's understand how to...
Iterators in Python – What are Iterators and Iterables?
Iterable in Python is any object that can be looped over. In order for an iterable to be looped over, an iterable needs to be converted to an...
Generators in Python – How to lazily return values only when needed and save memory?
Generators in python provide an efficient way of generating numbers or objects as and when needed, without having to store all the values in memory...
Decorators in Python – How to enhance functions without changing the code?
Decorators in python allow you to dynamically change the functionality of another function, without altering it's code.
Object Oriented Programming (OOPS) in Python
Object oriented programming is an effective way of writing code. Classes represent meaningful entities which defines its own behaviour (via methods)...
2021 2
Numpy Reshape – How to reshape arrays and what does -1 mean?
The numpy.reshape() is used to reshape a numpy array without changing the data in the array. Read on to know all about reshaping numpy arrays.
Vaex – Faster Pandas Alternate in Python
Vaex Python is an alternative to the Pandas library that take less time to do computations on huge data using Out of Core Dataframe. It has fast...
2020 9
Modin – How to speedup pandas by changing one line of code
Modin is a python library that can be used to handle large datasets using parallelisation. The syntax is similar to pandas and its astounding...
Dask – How to handle large dataframes in python using parallel computing
Learn how to use Dask to handle large datasets in Python using parallel computing. Covers Dask DataFrames, delayed execution, and integration with...
What does Python Global Interpreter Lock – (GIL) do?
Global Interpreter Lock (GIL) in python restricts multithreading. This post walks you behind the neccesity of GIL and how it it works.
Lambda Function in Python – How and When to use?
Learn how Python lambda functions work, when to use them, and how they differ from regular functions. Includes practical examples with map, filter...
Python Yield – What does the yield keyword do?
Adding yield keyword to a function will make the function return a generator object that can be iterated upon.
cProfile – How to profile your python code
Python Profilers, like cProfile helps to find which part of the program or code takes more time to run. This article will walk you through the...
Python Collections – An Introductory Guide
Collections is a built-in python module that provides useful container types. They allow us to store and access values in a convenient way...
Python JSON – Guide
JSON (JavaScript Object Notation) is a lightweight data format for exchanging data between languages. Learn how to serialize and deserialize JSON in...
Requests in Python Tutorial – How to send HTTP requests in Python?
Learn how to send HTTP requests in Python using the Requests library. Covers GET, POST, PUT, DELETE methods, headers, parameters, and response...
2019 2
datetime in Python – Simplified Guide with Clear Examples
datetime is the standard module for working with dates in python. It provides 4 main objects for date and time operations: datetime, date, time and...
Python Logging – Simplest Guide with Full Code and Examples
The logging module lets you track events while your code runs, so you can find what caused a crash from the logs. This post is a simple, clear guide...
2018 9
List Comprehensions in Python – My Simplified Guide
List comprehensions is a pythonic way of expressing a 'For Loop' that appends to a list in a single line of code. It is an intuitive, easy-to-read...
Python @Property Explained – How to Use and When? (Full Examples)
A python @property decorator lets a method to be accessed as an attribute instead of as a method with a '()'. Today, you will gain an understanding...
Parallel Processing in Python – A Practical Guide with Examples
Parallel processing is when the task is executed simultaneously in multiple processors. In this tutorial, you'll understand the procedure to...
101 Pandas Exercises for Data Analysis
Master pandas with 101 hands-on exercises across 3 difficulty levels. Practice data manipulation, filtering, grouping, and more to sharpen your...
pdb – How to use Python debugger
pdb, short for python debugger is a standard built-in module used to debug python code interactively. You can set breakpoints, see variable values...
101 NumPy Exercises for Data Analysis (Python)
The goal of the numpy exercises is to serve as a reference as well as to get you to apply numpy beyond the basics. The questions are of 4 levels of...
Numpy Tutorial Part 2 – Vital Functions for Data Analysis
This is part 2 of the mega numpy tutorial. In this part, I go into the details of the advanced features of numpy arrays that are essential for data...
Numpy Tutorial – Your first numpy guide to build python coding foundations
This is part 1 of the numpy tutorial covering all the core aspects of performing data manipulation and analysis with numpy's ndarrays. Numpy is the...
Python Regular Expressions Tutorial and Examples: A Simplified Guide
Regular expressions, also called regex, is a syntax or rather a language to search, extract and manipulate specific string patterns from a larger...