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Python Projects & Resources
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🐍 𝐏𝐲𝐭𝐡𝐨𝐧 𝐟𝐞𝐥𝐭 𝐢𝐦𝐩𝐨𝐬𝐬𝐢𝐛𝐥𝐞 𝐚𝐭 𝐟𝐢𝐫𝐬𝐭, 𝐛𝐮𝐭 𝐭𝐡𝐞𝐬𝐞 𝟗 𝐬𝐭𝐞𝐩𝐬 𝐜𝐡𝐚𝐧𝐠𝐞𝐝 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠!
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1️⃣ 𝐌𝐚𝐬𝐭𝐞𝐫𝐞𝐝 𝐭𝐡𝐞 𝐁𝐚𝐬𝐢𝐜𝐬: Started with foundational Python concepts like variables, loops, functions, and conditional statements.

2️⃣ 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐝 𝐄𝐚𝐬𝐲 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬: Focused on beginner-friendly problems on platforms like LeetCode and HackerRank to build confidence.

3️⃣ 𝐅𝐨𝐥𝐥𝐨𝐰𝐞𝐝 𝐏𝐲𝐭𝐡𝐨𝐧-𝐒𝐩𝐞𝐜𝐢𝐟𝐢𝐜 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬: Studied essential problem-solving techniques for Python, like list comprehensions, dictionary manipulations, and lambda functions.

4️⃣ 𝐋𝐞𝐚𝐫𝐧𝐞𝐝 𝐊𝐞𝐲 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬: Explored popular libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization.

5️⃣ 𝐅𝐨𝐜𝐮𝐬𝐞𝐝 𝐨𝐧 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬: Built small projects like a to-do app, calculator, or data visualization dashboard to apply concepts.

6️⃣ 𝐖𝐚𝐭𝐜𝐡𝐞𝐝 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: Followed creators like CodeWithHarry and Shradha Khapra for in-depth Python tutorials.

7️⃣ 𝐃𝐞𝐛𝐮𝐠𝐠𝐞𝐝 𝐑𝐞𝐠𝐮𝐥𝐚𝐫𝐥𝐲: Made it a habit to debug and analyze code to understand errors and optimize solutions.

8️⃣ 𝐉𝐨𝐢𝐧𝐞𝐝 𝐌𝐨𝐜𝐤 𝐂𝐨𝐝𝐢𝐧𝐠 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬: Participated in coding challenges to simulate real-world problem-solving scenarios.

9️⃣ 𝐒𝐭𝐚𝐲𝐞𝐝 𝐂𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐭: Practiced daily, worked on diverse problems, and never skipped Python for more than a day.

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#Python
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Loops in Python 👆
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⌨️ Learn About Python List Methods
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India won Champions Trophy 🏆🎉
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Python for Everything:

Python + Django = Web Development

Python + Matplotlib = Data Visualization

Python + Flask = Web Applications

Python + Pygame = Game Development

Python + PyQt = Desktop Applications

Python + TensorFlow = Machine Learning

Python + FastAPI = API Development

Python + Kivy = Mobile App Development

Python + Pandas = Data Analysis

Python + NumPy = Scientific Computing
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Python Libraries for Data Science
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How to master Python from scratch🚀

1. Setup and Basics 🏁
   - Install Python 🖥️: Download Python and set it up.
   - Hello, World! 🌍: Write your first Hello World program.

2. Basic Syntax 📜
   - Variables and Data Types 📊: Learn about strings, integers, floats, and booleans.
   - Control Structures 🔄: Understand if-else statements, for loops, and while loops.
   - Functions 🛠️: Write reusable blocks of code.

3. Data Structures 📂
   - Lists 📋: Manage collections of items.
   - Dictionaries 📖: Store key-value pairs.
   - Tuples 📦: Work with immutable sequences.
   - Sets 🔢: Handle collections of unique items.

4. Modules and Packages 📦
   - Standard Library 📚: Explore built-in modules.
   - Third-Party Packages 🌐: Install and use packages with pip.

5. File Handling 📁
   - Read and Write Files 📝
   - CSV and JSON 📑

6. Object-Oriented Programming 🧩
   - Classes and Objects 🏛️
   - Inheritance and Polymorphism 👨‍👩‍👧

7. Web Development 🌐
   - Flask 🍼: Start with a micro web framework.
   - Django 🦄: Dive into a full-fledged web framework.

8. Data Science and Machine Learning 🧠
   - NumPy 📊: Numerical operations.
   - Pandas 🐼: Data manipulation and analysis.
   - Matplotlib 📈 and Seaborn 📊: Data visualization.
   - Scikit-learn 🤖: Machine learning.

9. Automation and Scripting 🤖
   - Automate Tasks 🛠️: Use Python to automate repetitive tasks.
   - APIs 🌐: Interact with web services.

10. Testing and Debugging 🐞
    - Unit Testing 🧪: Write tests for your code.
    - Debugging 🔍: Learn to debug efficiently.

11. Advanced Topics 🚀
    - Concurrency and Parallelism 🕒
    - Decorators 🌀 and Generators ⚙️
    - Web Scraping 🕸️: Extract data from websites using BeautifulSoup and Scrapy.

12. Practice Projects 💡
    - Calculator 🧮
    - To-Do List App 📋
    - Weather App ☀️
    - Personal Blog 📝

13. Community and Collaboration 🤝
    - Contribute to Open Source 🌍
    - Join Coding Communities 💬
    - Participate in Hackathons 🏆

14. Keep Learning and Improving 📈
    - Read Books 📖: Like "Automate the Boring Stuff with Python".
    - Watch Tutorials 🎥: Follow video courses and tutorials.
    - Solve Challenges 🧩: On platforms like LeetCode, HackerRank, and CodeWars.

15. Teach and Share Knowledge 📢
    - Write Blogs ✍️
    - Create Video Tutorials 📹
    - Mentor Others 👨‍🏫

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Python Mindmap
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How to convert image to pdf in Python

# Python3 program to convert image to pfd
# using img2pdf library
 
# importing necessary libraries
import img2pdf
from PIL import Image
import os
 
# storing image path
img_path = "Input.png"
 
# storing pdf path
pdf_path = "file_pdf.pdf"
 
# opening image
image = Image.open(img_path)
 
# converting into chunks using img2pdf
pdf_bytes = img2pdf.convert(image.filename)
 
# opening or creating pdf file
file = open(pdf_path, "wb")
 
# writing pdf files with chunks
file.write(pdf_bytes)
 
# closing image file
image.close()
 
# closing pdf file
file.close()
 
# output
print("Successfully made pdf file")

pip3 install pillow && pip3 install img2pdf
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⌨️ Hide secret message in image using Python
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⌨️ Grammar Correction using Python
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Happy Holi Guys 🎨🎆
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Don't overwhelm to learn Git,🙌

Git is only this much👇😇


1.Core:
• git init
• git clone
• git add
• git commit
• git status
• git diff
• git checkout
• git reset
• git log
• git show
• git tag
• git push
• git pull

2.Branching:
• git branch
• git checkout -b
• git merge
• git rebase
• git branch --set-upstream-to
• git branch --unset-upstream
• git cherry-pick

3.Merging:
• git merge
• git rebase

4.Stashing:
• git stash
• git stash pop
• git stash list
• git stash apply
• git stash drop

5.Remotes:
• git remote
• git remote add
• git remote remove
• git fetch
• git pull
• git push
• git clone --mirror

6.Configuration:
• git config
• git global config
• git reset config

7. Plumbing:
• git cat-file
• git checkout-index
• git commit-tree
• git diff-tree
• git for-each-ref
• git hash-object
• git ls-files
• git ls-remote
• git merge-tree
• git read-tree
• git rev-parse
• git show-branch
• git show-ref
• git symbolic-ref
• git tag --list
• git update-ref

8.Porcelain:
• git blame
• git bisect
• git checkout
• git commit
• git diff
• git fetch
• git grep
• git log
• git merge
• git push
• git rebase
• git reset
• git show
• git tag

9.Alias:
• git config --global alias.<alias> <command>

10.Hook:
• git config --local core.hooksPath <path>

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