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@clcoding_python · group · Tech · indexed since 2026-07-13
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Python for Data Analysis — Free PDF Want to take your Python skills into real-world data analysis? This 905-page guide covers a wide range of topics around: Python for Data Analysis Data Analytics & Visualization Advanced Models Automation & Scalable Data Workflows Practical tools and techniques for modern data work A useful resource for Python developers, data analysts, and anyone building skills in data science. Free PDF: https://www.clcoding.com/2026/07/python-for-data-analysis-modern-guide.html
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Python Pattern Challenge — Day 17 Another day, another Python pattern to solve! Pattern problems may look simple, but they’re a great way to practice: • Nested loops • range() • Logic building • Spacing & formatting • Problem-solving skills The goal isn’t just to print a pattern — it’s to understand how Python builds it step by step. Can you solve today’s pattern without looking at the solution? Day 17: https://www.clcoding.com/2026/10/python-pattern-challenge-day-17.html
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The real Python developer life! Write the code → Run the code → Get an error → Google the error → Try the solution → Fix one tiny bug → Suddenly everything works! And then you sit back like you just solved a billion-dollar problem. Debugging isn’t a side quest in programming… it’s the main storyline. https://link.amazon/B0gPOzQkt
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Python Coding Challenge — Day 1270 Can you predict the output of this Python code without running it? These small Python puzzles are a great way to improve your understanding of: • Python execution flow • Data types & expressions • Common Python tricks • Interview-style problem solving Take a few seconds and think carefully before checking the answer. Challenge: https://www.clcoding.com/2026/10/python-coding-challenge-day-1270-what.html Drop your answer in the comments! 👇
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Turn a PDF into a Visual Data Story with Python! Ever wondered how many words are on each page of a PDF? With just a few lines of Python, you can: Read a PDF using PyMuPDF (fitz) Count words on every page Create a page-by-page bar chart with Matplotlib Quickly identify pages with more or less text This is a simple example of how Python can turn raw PDF content into useful visual insights. Perfect for PDF analysis, document processing, automation, and data visualization. Save this code for your next PDF automation project! Projects: https://link.amazon/B00cQoeY0
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Microsoft Python Development Professional Certificate Want to build stronger Python development skills and learn through a structured professional program? This certificate covers practical Python development concepts and can be a useful resource for learners looking to strengthen their programming foundation and move toward real-world development. Learn Python Build development skills Follow a structured learning path Practice with real-world concepts Strengthen your developer portfolio 🔗 Check out the full details here: https://www.clcoding.com/2025/05/microsoft-python-development.html
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Every Python project ever: You start with confidence: “Today I’ll build something amazing!” Then Python throws an error and suddenly you're questioning every decision you've ever made. Next comes the real development process: Google Stack Overflow YouTube ChatGPT After 47 tabs, 3 cups of coffee, and absolutely no idea what changed… IT WORKS! And yes, sometimes the most important programming skill is simply knowing which error to Google. Projects: https://gumroad.com/products/noioiq/
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Python Pattern Challenge — Day 18 Think you know Python? Try solving this pattern without looking at the solution 👀 Pattern problems are a simple but powerful way to improve your understanding of: 🔹 Nested loops 🔹 range() 🔹 Logic building 🔹 Rows & columns 🔹 Spaces and formatting 🔹 Problem-solving skills Your challenge: Look at the pattern, understand the logic, and write the Python code yourself. Don’t just memorize the solution — understand why each loop works. Day 18 of the Python Pattern Challenge 👉 Try it first, then compare your approach with the solution. https://www.clcoding.com/2026/10/python-pattern-challenge-day-18.html
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Did you know Python has a design philosophy? Python isn’t just about getting code to work — it was designed to make code readable, simple, and elegant. This displays The Zen of Python, a collection of principles that guide Python’s design. A few favorites: ✨ Beautiful is better than ugly. ✨ Explicit is better than implicit. ✨ Simple is better than complex. ✨ Readability counts. ✨ There should be one — and preferably only one — obvious way to do it. That’s one reason Python feels so natural to read and write. Good code isn’t just code that works. Good code is code that humans can understand. https://link.amazon/B05mhPoC1
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📘 Pen and Paper Exercises in Machine Learning — FREE PDF Want to strengthen your Machine Learning fundamentals without relying only on coding? This 211-page book is packed with pen-and-paper exercises designed to help you understand the mathematics, concepts, and reasoning behind Machine Learning. Perfect for: • ML beginners • Data Science students • Anyone revising ML fundamentals • Learners preparing for interviews & exams Learn the concepts. Solve the problems. Build stronger ML intuition. Free PDF: https://www.clcoding.com/2026/08/pen-and-paper-exercises-in-machine.html
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Turn your Python data into a beautiful story with Plotnine! If you’re familiar with ggplot2, Plotnine brings the same grammar-of-graphics approach to Python. With just a few lines of code, you can: Create clean and professional charts Visualize Pandas DataFrames Customize titles, labels, colors & themes Build charts using ggplot() + geom_*() ✨ Turn raw data into visuals that are easy to understand The example above creates a simple Programming Language Popularity bar chart using Plotnine and Pandas. Code → Data → Visualization → Story. Save this if you're learning Python, Pandas & Data Visualization. https://link.amazon/B0jbKKENK
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Every Python developer has been here! You write your code. Everything looks perfect. You change ONE line… Suddenly: ERROR! You check the logic. You check the syntax. You check the variable names. You question your entire programming career. And then you find it: 👉 Indentation. That one tiny space was responsible for all the drama. Python lesson: Indentation isn’t just formatting — it’s part of the syntax. Save this for the next time Python makes you question your life. https://gumroad.com/products/tyysv/
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Deep Learning Methods of Mathematical Physics — Volume I Interested in the intersection of Deep Learning, Mathematics, and Physics? This 461-page resource explores how modern deep learning techniques can be applied to direct and inverse problems in mathematical physics. 🔹 Deep Learning & Mathematical Physics 🔹 Direct & Inverse Problems 🔹 Mathematical modeling 🔹 Scientific computing 🔹 Physics-informed approaches 🔹 461 pages of learning material A useful resource for students, researchers, data scientists, and anyone exploring AI + Mathematics + Physics. Free PDF: https://www.clcoding.com/2026/07/deep-learning-methods-of-mathematical.html
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اینم از جلسه نهم با زبان C 😎 • این قسمت می‌خوایم با یکی از قابلیت‌های باحال و کاربردی زبان C آشنا بشیم: ساختارها یا همون struct. • ساختارها بهمون کمک می‌کنن چندتا داده با نوع‌های مختلف رو کنار هم نگه داریم. مثلاً برای ثبت اطلاعات یک دانشجو، می‌تونیم اسم، شمارهٔ دانشجویی و معدلش رو توی یک ساختار قرار بدیم. ▎ 1. سینتکس تعریف ساختار ساختار رو به این شکل تعریف می‌کنیم: struct StructureName { data_type member1; data_type member2; }; • struct مشخص می‌کنه که داریم یک ساختار تعریف می‌کنیم. • StructureName اسم ساختاره. • member ها هم داده‌هایی هستن که داخل ساختار نگه می‌داریم.  ▎ 2. یک مثال ساده بیایین یک ساختار برای اطلاعات دانشجو بسازیم: #include <stdio.h> struct Student { char name[50]; int studentNumber; float average; }; int main() { struct Student student1 = {"Sara", 12345, 18.75}; printf("Name: %s\n", student1.name); printf("Student number: %d\n", student1.studentNumber); printf("Average: %.2f\n", student1.average); return 0; } • اینجا Student اسم ساختاره و name، studentNumber و average عضوهای اون هستن. • با نوشتن struct Student student1 یک متغیر از نوع ساختار Student می‌سازیم. ▎ 3. دسترسی به عضوهای ساختار برای دسترسی به عضوهای یک متغیر ساختاری، از نقطه (.) استفاده می‌کنیم: student1.studentNumber = 54321; student1.average = 19.25; • مثلاً student1.average یعنی عضو average از متغیر student1. ▎ 4. استفاده از ساختار به‌عنوان ورودی تابع ساختارها رو می‌تونیم به تابع هم بفرستیم: #include <stdio.h> struct Student { char name[50]; int studentNumber; float average; }; void printStudent(struct Student student) { printf("Name: %s\n", student.name); printf("Average: %.2f\n", student.average); } int main() { struct Student student1 = {"Sara", 12345, 18.75}; printStudent(student1); return 0; } • توی این مثال، تابع printStudent یک متغیر از نوع struct Student می‌گیره و اطلاعاتش رو چاپ می‌کنه. ▎ نکته مهم 🔍 • یادتون باشه بعد از آکولاد پایانیِ تعریف ساختار، باید ; بذارین. ▎ نکت
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📊 Make Your Python Data Interactive! Want to turn a Pandas DataFrame into an interactive visualization with just a few lines of code? Meet HoloViews + hvPlot — a powerful combination for creating interactive charts without writing complex plotting code. ✨ Why hvPlot? Interactive charts with minimal code Works naturally with Pandas Zoom, pan, hover & explore your data Great for dashboards and data exploration Built on the HoloViz ecosystem Instead of static charts, let your data become interactive. https://link.amazon/B0chJmgkp
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Python Pattern Challenge — Day 19 Think you’re good at Python loops? This pattern challenge might make you think twice! Your challenge: Can you predict the pattern and write the Python code to generate it? Don’t just look at the output — understand the logic behind the pattern. Practice: • for loops • Nested loops • range() • Pattern logic • Problem-solving skills Day 19 of the Python Pattern Challenge is here! 👉 Try it yourself before checking the solution: https://www.clcoding.com/2026/10/python-pattern-challenge-day-19.html
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Python + Generative Art = Creative Coding! Who said Python is only for data science and automation? With just a few lines of Python, you can create generative artwork and turn it into a PDF. This example uses PyMuPDF (fitz) + random to: Generate 100 random circles Create a unique visual pattern Draw everything directly into a PDF Add custom Python-themed text Save the final artwork as a PDF The best part? Every run can create a different design because the positions and sizes are randomized. Python isn't just about solving problems — it's also a tool for creativity. https://link.amazon/B08YMfC6u
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You are preparing a presentation when one dashboard freezes every time you open it. Other websites remain fast, so the computer seems fine. The dashboard could be waiting on an API, DNS lookup, authentication request, old script, or browser extension. Before buying faster hardware, finding the exact delay could tell you whether the computer was ever the problem. https://f4y78oSF3s.linkas.net
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Big Data and AI Strategies: Machine Learning and Alternative Data Approach to Investing Want to explore how Big Data, Artificial Intelligence, Machine Learning, and alternative data are transforming modern investing? This 280-page book explores how data-driven techniques can be applied to investment research, financial analysis, and decision-making. What you’ll explore: • Big Data in finance • AI & Machine Learning for investing • Alternative data sources • Data-driven investment strategies • Machine learning applications in financial markets • The future of AI-powered investing Free PDF: https://www.clcoding.com/2026/08/big-data-and-ai-strategies-machine.html
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