Python learning
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📈 Аналитический обзор Telegram-канала Python learning
Канал Python learning (@python3learning) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 22 882 подписчиков, занимая 8 592 место в категории Образование и 18 283 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 22 882 подписчиков.
Согласно последним данным от 25 августа, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -259, а за последние 24 часа — -11, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 6.20%. В первые 24 часа после публикации контент обычно набирает N/A% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 0 просмотров. В течение первых суток публикация набирает 0 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 0.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Learn python🔥”
Благодаря высокой частоте обновлений (последние данные получены 26 августа, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.
22 882
Подписчики
-1124 часа
-667 дней
-25930 день
Архив постов
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Top 10 Python Libraries for Data Science
🐍 NumPy – Fast array operations and numerical computing
📊 Pandas – Data manipulation using DataFrames
📈 Matplotlib – Plotting and basic data visualization
🎨 Seaborn – Statistical plots built on Matplotlib
🧠 Scikit-learn – Machine learning models and tools
🤖 TensorFlow – Deep learning library by Google
🔥 PyTorch – Flexible deep learning by Facebook
📉 Statsmodels – Statistical tests and data exploration
🚀 XGBoost – Powerful boosting algorithm for structured data
🌐 Plotly – Interactive and web-ready visualizations
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Stanford’s Machine Learning - by Andrew Ng
A complete lecture notes of 227 pages. Available Free.
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Git Commands
🛠 git init – Initialize a new Git repository
📥 git clone <repo> – Clone a repository
📊 git status – Check the status of your repository
➕ git add <file> – Add a file to the staging area
📝 git commit -m "message" – Commit changes with a message
🚀 git push – Push changes to a remote repository
⬇️ git pull – Fetch and merge changes from a remote repository
Branching
📌 git branch – List all branches
🌱 git branch <name> – Create a new branch
🔄 git checkout <branch> – Switch to a branch
🔗 git merge <branch> – Merge a branch into the current branch
⚡️ git rebase <branch> – Apply commits on top of another branch
Undo & Fix Mistakes
⏪ git reset --soft HEAD~1 – Undo the last commit but keep changes
❌ git reset --hard HEAD~1 – Undo the last commit and discard changes
🔄 git revert <commit> – Create a new commit that undoes a specific commit
Logs & History
📖 git log – Show commit history
🌐 git log --oneline --graph --all – View commit history in a simple graph
Stashing
📥 git stash – Save changes without committing
🎭 git stash pop – Apply stashed changes and remove them from stash
Remote & Collaboration
🌍 git remote -v – View remote repositories
📡 git fetch – Fetch changes without merging
🕵️ git diff – Compare changes
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This Python Data Type Cheatsheet provides a comparison of five key data structures:
1. String (str)
Immutable (cannot be changed)
Ordered and indexed
Allows duplicate characters
Example: my_str = "Hello"
2. List (list)
Mutable (can be changed)
Ordered and indexed
Allows duplicate elements
Example: my_list = ["Hello", "World"]
Can store different data types
3. Tuple (tuple)
Immutable
Ordered and indexed
Allows duplicates
Example: my_tuple = ("Hello", "World")
Can store different data types
4. Set (set)
Mutable
Unordered
Does not allow duplicates
Example: my_set = {"Hello", "World"}
Can store int, str, tuple, but not list, set, or dict
5. Dictionary (dict)
Mutable
Unordered
Does not allow duplicate keys
Example: my_dict = {"greeting": "Hello", "salutation": "World"}
Keys can be int, str, tuple, but not list, set, or dict
Values can be any data type
This cheatsheet helps in understanding the properties and use cases of each data type in Python.
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The <input> tag in HTML is used to collect user input in web forms. Here are some key points about it:
Versatile Usage – Supports multiple input types like text, password, number, email, date, etc.
User Interaction – Enables users to enter or select data for forms.
Customizable – Can include attributes like placeholder, required, disabled, and readonly to control behavior.
Form Submission – Works with the <form> tag to send user data to a server.
Validation Support – Helps validate input using attributes like maxlength, pattern, min, and max.
Enhanced UX – Improves usability with features like auto-focus, default values, and autocomplete.
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Full-Stack Web Developer Roadmap🚀🔥
✅ Day 1-25: HTML, CSS, JS.
✅ Day 26-40: React JS.
✅ Day 41-55: Node JS & Express.
✅ Day 56-70: MongoDB.
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📍 Python Roadmap for Beginners
|_ 🐍 Introduction to Python
|_ 📦 Modules, Comments, & Pip
|_ 🔢 Variables, Data Types, Keywords & Operators
|_ 📊 Python Data Types in Detail
|_ 🔁 Flow Control in Python
|_ 🔄 Loops in Python
|_ 📝 String Operations (Advanced)
|_ 🏗 Functions in Python
|_ 📂 File Handling in Python
|_ 🏛 Object-Oriented Programming (OOP)
|_ ⚠️ Exception Handling
]
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Bank management system using python complete source code https://inprogrammer.com/bank-management-sytem-using-python-complete-code/
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