ggplot in Python with plotnine

🐍📈 Data Visualization With Python In this learning path, you'll see how you can use Python to turn your data into clear and useful visualizations so that you can share your findings more effectively #python #learnpython

Many Python I/O tutorials end at print() and open(). This one goes further. On PythonCodeCrack there's a full beginner tutorial on Python I/O that covers the ground many skip — not just how to use the tools, but why they work the way they do. What's inside: — stdin, stdout, and stderr: what they are, where they come from, and why Python didn't invent them — print() in full: sep, end, flush, and why flush=True doesn't mean your data is on disk — input() and why it always returns a string no matter what the user types — File modes r, w, a, and x — including why 'w' truncates before the first write, not during it — The three-layer CPython I/O stack (TextIOWrapper → BufferedWriter → FileIO) and how to inspect it live — PEP 393: why a single emoji in a 2 GB text file can force 4 bytes per character across the entire string — buffering=1 line-buffered mode for crash-safe log files — flush() vs os.fsync() — two entirely different operations that most tutorials treat as the same thing — Python 3.15 making UTF-8 the default on all platforms, and what that means for existing code — sys.__stdout__ vs sys.stdout, newline translation, file descriptors, and TOCTOU race conditions The tutorial includes interactive quizzes, spot-the-bug challenges, a code builder, predict-the-output exercises, a 15-question final exam, and a downloadable certificate of completion. https://lnkd.in/gbYPmYgv #Python #PythonProgramming #LearnPython #CodingEducation

NumPy vs Pure Python: A 3.3x SpeedUp I just benchmarked calculating mean, median, and mode on 10,000 numbers: Pure Python: 0.141 seconds NumPy: 0.043 seconds Speedup: 3.3x "But wait... isn't NumPy just Python too?" Actually, I was surprised: shouldn't pure Python be faster since NumPy is built on top of Python? Then I searched for why this actually happened and what's going on under the hood. That means: 1. Implementing from scratch takes more time to write code 2. Implementing from scratch takes more time to execute code Here's what's actually happening under the hood: 1️⃣ VECTORIZATION Pure Python: Loops through each element (interpreter overhead) NumPy: C-compiled operations on entire arrays 2️⃣ MEMORY EFFICIENCY Python lists: Scattered pointers across memory NumPy arrays: Contiguous blocks → cache-friendly 3️⃣ ZERO TYPE OVERHEAD Python: Type-checks every element, every operation NumPy: Homogeneous arrays → check once 4️⃣ CPU-LEVEL OPTIMIZATION NumPy leverages SIMD instructions (process multiple numbers simultaneously) Code: https://lnkd.in/g7wsVFXp #Python #DataScience #Performance #NumPy #Programming #MachineLearning

🕸️ Built a Web Scraper using Python! 🚀 I recently created a simple project where I extracted quotes and author names from a website using Python. 💡What this project does: • Scrapes data (quotes & authors) from a website • Uses BeautifulSoup and requests • Stores the extracted data in CSV format This project gave me a better understanding of how websites work behind the scenes. 🔗 GitHub Project:https://lnkd.in/dzYvPjCi Synent Technologies #Python #WebScraping #BeginnerProject #Coding #Learning #GitHub

🚀 Python Series – Day 2: Installing Python & Writing Your First Program Yesterday, we understood What is Python & Why it is powerful. Today, let’s take the first real step— installing Python and writing your first program 💻 🔧 Step 1: Install Python 1. Go to the official website: https://www.python.org 2. Download the latest version 3. While installing, IMPORTANT: ✔️ Check “Add Python to PATH” ▶️ Step 2: Verify Installation Open Command Prompt / Terminal and type: python --version 🧠 Step 3: Your First Python Program print("Hello, World!") 💡 What does this mean? print() → Used to display output "Hello, World!"→ Text (string) 🎯 Why is this important? This is your first step into coding. Every expert once started with this simple line. 🔥 Pro Tip: Try this: print("I am learning Python 🚀") ❓ Question for you: Have you written your first Python program yet? 👉 Comment YES / NO— I’d love to know! 📌 Tomorrow: Variables & Data Types (Most Important Topic!) #Python #DataScience #Coding #Programming #LearnPython #Beginners #Tech #MustaqeemSiddiqui

DAY 2 – #LearningInPublic (Python Basics) 🧠 Today’s Focus: My First Calculation in Python ✅ Every programming journey starts with something small — today I wrote my first Python calculation using variables and addition. Here’s what I learned: 📌 Step 1: Create Variables I stored numbers inside variables: • a = 10 • b = 10 Variables act like containers that hold values. 📌 Step 2: Perform Calculation I added both variables: sum = a + b Python calculated the result and stored it in a new variable called sum. 📌 Step 3: Print Output Finally, I displayed the result using print(): Output: 20 Wow You have done your first calculation in Python 💡 Key Concepts Learned • Variables • Assignment operator (=) • Addition operator (+) • Storing results in variables • print() function • Running first Python program This may look simple, but this is the foundation of everything in Python: Data Science Machine Learning AI Automation Web Development Every advanced system starts with basic calculations like this. Small steps. Big journey ahead. 🚀 #LearningInPublic #Python #PythonBeginner #DataScience #AI #Programming #100DaysOfCode #DeveloperJourney #MachineLearning #AIEngineering

A quick refresher on Statistics in Python! From basics like mean & median to advanced topics like hypothesis testing and distributions, this guide neatly covers the key functions every data analyst should know. Definitely a handy reference for real-world data analysis 💡 #DataAnalytics #Python #Statistics

Built a simple calculator using Python 🧮 Recently completed the basics of: • Variables • User Input • Conditional Statements (if/elif/else) Applied these concepts to create this small project. Looking forward to building more as I continue learning Python 🚀 Here’s the code: ```python a = int(input("what is first value: ")) b = input("what you want to do: ") c = int(input("what is second value: ")) if b == "+": print("your result is", a + c) elif b == "-": print("your result is", a - c) elif b == "*": print("your result is", a * c) elif b == "/": print("your result is", a / c) ``` #Python #CodingJourney #BeginnerProject #LearningByDoing

🐍📰 Working With Files in Python In this tutorial, you'll learn how you can work with files by using built-in modules to perform practical tasks that involve groups of files, like renaming them, moving them, getting their metadata,and more. #python

Finally, PYTHON ADVANCED TUTORIAL FOR DATA DOMAIN is out! - You should ONLY watch this if you already know the basics - loops, if-else, lists, etc. We aren't doing "Hello World" here. This course is built for one thing: Real-world Python use cases. If you’re building anything in the Data Domain, these are non-negotiable skills. We are going to teach everything from SCRATCH, but we’re jumping directly into the real stuff. If you’ve been looking to upskill your Python game, this is for YOU. A small note: Pandas and PySpark are NOT covered here. We are focusing purely on Advanced Python. - Why? Because even if you want to work with Pandas or PySpark, you first need to know how to use the underlying utilities. Those "childish" transformations are not enough to build production-grade pipelines. Stop scratching the surface and start building. 📍 Find the link in the COMMENTS below!