Python Coding (CLCODING)
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Learn Python to automate your things. We are here to support you. Ask your question

Reach us - info@clcoding.com

https://whatsapp.com/channel/0029Va5BbiT9xVJXygonSX0G
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πŸ’» How I Think Coding Will Go… vs. Reality

Projects: https://amzn.to/4xFOJIJ
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Visualize Major USA Cities with Python & Contextily

Want to turn geographic data into a beautiful map with Python?

πŸ—Ί With just a few lines of code, you can combine GeoPandas, Shapely, Matplotlib, and Contextily to plot major U.S. cities on a real-world map.

πŸ“ Cities included:

New York
Los Angeles
Chicago

What this project demonstrates

β€’ Creating geographic points with Shapely

β€’ Managing spatial data with GeoPandas

β€’ Converting coordinates to Web Mercator (EPSG:3857)

β€’ Adding OpenStreetMap basemaps with Contextily

β€’ Labeling cities on a geographic visualization

Python for GIS & Spatial Intelligence: amzn.to/3UCfFe1
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Python Quiz of the Day

Python Coding Challenge - Question with Answer (ID 090926)

Answer with Explanation: https://www.clcoding.com/2026/09/python-coding-challenge-id-090926.html
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Google AI+ is free for students.

Duration: 1 Years

they can claim here.

https://www.clcoding.com/2026/09/google-ai-student-offer-2026-get-google.html
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September Data Science Bootcamp

Day 5 is all about Functions in Python β€” one of the most important concepts for writing clean, reusable, and maintainable code.

Join Free: https://youtube.com/live/1PENRkAmOxg?feature=share

In today’s session, we’ll learn:

What are Python functions?
Defining and calling functions
Parameters and arguments
Return values
Default and keyword arguments
*args and **kwargs
Local vs global variables
Lambda functions
Practical examples for Data Science

Functions help you break complex problems into smaller, reusable pieces β€” a skill every Data Scientist and Python Developer needs.

Keep learning. Keep coding.
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πŸ“˜ Introduction to Probability for Data Science β€” Free PDF

Want to build a strong foundation in Data Science, Machine Learning, and AI?

This 691-page book provides a comprehensive introduction to probability with a focus on data science applications. It covers topics including:

β€’ Mathematical foundations
β€’ Probability and conditional probability
β€’ Random variables
β€’ Discrete & continuous distributions
β€’ Joint distributions
β€’ Sample statistics
β€’ Regression
β€’ Estimation
β€’ Confidence intervals & hypothesis testing
β€’ Random processes
β€’ Probability in Machine Learning

Probability is more than formulas β€” it helps you reason about uncertainty, data, predictions, and real-world outcomes.

πŸ“š 691 Pages
🎯 Ideal for Data Science & Machine Learning learners
πŸ’» Free PDF

Read and access the book here:
https://www.clcoding.com/2026/09/introduction-to-probability-for-data.html
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🌐 Live Website Status Dashboard

Projects: https://amzn.to/3V6R3dr
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🐍 Python Coding Challenge – ID 100926

Can you predict the output before running the code?

Answer with Explanation: https://www.clcoding.com/2026/09/python-coding-challenge-id-100926.html
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September Data Science Bootcamp | Day 6 🐍
Exception & File Handling πŸ’»

Join Free: https://youtube.com/live/HTYbKVl2KFU?feature=share

Learn how to write more reliable Python programs with:
πŸ”Ή try-except & exception handling
πŸ”Ή CSV & JSON files
πŸ”Ή File handling basics
πŸ”Ή pathlib and file paths

Learn β†’ Practice β†’ Build β†’ Grow πŸš€
What can Python do for Chemical Engineering?

Here are 5 powerful Cantera programs to find out!

pip intsall cantera

https://x.com/clcoding/status/2097908878818283957?s=20

Follow @pythonclcoding
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PDF β†’ Automatic Metadata Report πŸ“„πŸ

Turn a PDF into a quick metadata report with Python.

Python + PDFs = powerful automation. πŸš€

https://amzn.to/3UHwa8B
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PDF β†’ Automatic Metadata Report πŸ“„πŸ

Turn a PDF into a quick metadata report with Python.

Python + PDFs = powerful automation. πŸš€

https://amzn.to/3UHwa8B
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Differential Geometry β€” Free PDF

Learn the mathematics of curves, surfaces, manifolds, curvature, geodesics, and tensors with this free Differential Geometry resource.

πŸ“˜ Topics include:

Curves and surfaces
Tangent vectors and tangent spaces
Curvature and torsion
Geodesics
Riemannian geometry
Differential forms
Manifolds and tensors
Applications in physics and mathematics

Detailed Explanation: https://www.clcoding.com/2026/09/differential-geometry-free-pdf.html

Perfect for mathematics, physics, engineering, and data science students looking to build a stronger foundation in advanced geometry.
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Experience is the teacher of all things, while certification is proof of your dedication and expertise. Let’s explore the key points about both:

https://x.com/clcoding/status/2098145738240987425?s=20
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Python Quiz of the Day

Python Coding Challenge - Question with Answer (ID 110926)

Answer with Explanation: https://www.clcoding.com/2026/09/python-coding-challenge-id-110926.html
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September Data Science Bootcamp | OOP Essentials

We’re LIVE on YouTube!
https://youtube.com/live/SeX9wHN88pE

Join us for an interactive session on Object-Oriented Programming (OOP) in Python.

Today’s focus: Classes, Objects & Constructors
Watch live, learn, practice, and build real Python skills.
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Interactive Profile Dashboard with Streamlit

Build a personal profile dashboard where users can explore:

Projects: https://amzn.to/4hoi30F

Profile: Name, photo, bio, skills
About: Education, experience, achievements
Skills: Interactive skill bars or charts
Projects: Project cards with GitHub/demo links
Experience: Interactive timeline
Contact: Email and social links
Analytics: Skills, projects, experience, and other profile statistics

Tech Stack: Python + Streamlit + Pandas + Plotly
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