ch
Feedback
Python Interviews

Python Interviews

前往频道在 Telegram

Join this channel to learn python for web development, data science, artificial intelligence and machine learning with quizzes, projects and amazing resources for free For collaborations: @coderfun

显示更多

📈 Telegram 频道 Python Interviews 的分析概览

频道 Python Interviews (@pythoninterviews) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 28 768 名订阅者,在 技术与应用 类别中位列第 4 787,并在 印度 地区排名第 15 187

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 28 768 名订阅者。

根据 05 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 88,过去 24 小时变化为 6,整体触达仍然可观。

  • 认证状态: 未认证
  • 互动率 (ER): 平均受众互动率为 0.63%。内容发布后 24 小时内通常能获得 0.81% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 181 次浏览,首日通常累积 234 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 1
  • 主题关注点: 内容集中在 |--, link:-, learning, sql, analytic 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台:
Join this channel to learn python for web development, data science, artificial intelligence and machine learning with quizzes, projects and amazing resources for free For collaborations: @coderfun

凭借高频更新(最新数据采集于 07 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。

28 768
订阅者
+624 小时
+147
+8830
帖子存档
Python List Methods
Python List Methods

Hello Everyone, 𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 𝗼𝗻 𝗔𝗜/𝗠𝗟 😍 🌟 Kickstart Your Artificial Intelligence & Ma
Hello Everyone,  𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 𝗼𝗻 𝗔𝗜/𝗠𝗟 😍 🌟 Kickstart Your Artificial Intelligence & Machine Learning Career 📚 Roadmap to Become a Successful AI & ML Engineer 👥 Eligibility: Students, Freshers & Working Professionals 📝𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐍𝐨𝐰 𝐟𝐨𝐫 𝐅𝐑𝐄𝐄👇:-  https://bit.ly/3W72css ⏳ Limited Slots Available – Hurry Up! 🏃‍♂️ 📅 Date & Time: Jan 09, 2025, at 7 PM Don’t miss out on this opportunity to shape your future in AI & ML! 💻✨

⌨️ Quick Python cheatsheet.
⌨️ Quick Python cheatsheet.

Python In Action ❤️‍🔥

Top 5 Tools to master Data Analytics 1. Python: - Versatile programming language. - Offers powerful libraries like Pandas, NumPy, and Scikit-learn. - Used for data manipulation, analysis, and machine learning tasks. 2. R: - Statistical programming language. - Provides extensive statistical capabilities. - Popular for data analysis in academia. - Offers visualization libraries like ggplot2. 3. SQL (Structured Query Language): - Essential for working with relational databases. - Allows querying, manipulation, and management of data. - Standard language for database management systems. 4. Tableau: - Data visualization tool. - Enables creation of interactive dashboards. - Helps in communicating insights effectively. - Widely used in business intelligence. 5. Apache Spark: - Framework for large-scale data processing. - Offers distributed computing capabilities. - Libraries like Spark SQL and MLlib for data manipulation and machine learning. - Ideal for processing big data efficiently. I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://topmate.io/analyst/861634

𝐒𝐭𝐫𝐢𝐧𝐠 𝐌𝐚𝐧𝐢𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧: Strings in Python are immutable sequences of characters. 𝟏- 𝐥𝐞𝐧(): 𝐑𝐞𝐭𝐮𝐫𝐧𝐬 𝐭𝐡𝐞 𝐥𝐞𝐧𝐠𝐭𝐡 𝐨𝐟 𝐭𝐡𝐞 𝐬𝐭𝐫𝐢𝐧𝐠. my_string = "Hello" length = len(my_string)  # length will be 5 𝟐- 𝐬𝐭𝐫(): 𝐂𝐨𝐧𝐯𝐞𝐫𝐭𝐬 𝐧𝐨𝐧-𝐬𝐭𝐫𝐢𝐧𝐠 𝐝𝐚𝐭𝐚 𝐭𝐲𝐩𝐞𝐬 𝐢𝐧𝐭𝐨 𝐬𝐭𝐫𝐢𝐧𝐠𝐬. num = 123 str_num = str(num)  # str_num will be "123" 𝟑- 𝐥𝐨𝐰𝐞𝐫() 𝐚𝐧𝐝 𝐮𝐩𝐩𝐞𝐫(): 𝐂𝐨𝐧𝐯𝐞𝐫𝐭 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠 𝐭𝐨 𝐥𝐨𝐰𝐞𝐫𝐜𝐚𝐬𝐞 𝐨𝐫 𝐮𝐩𝐩𝐞𝐫𝐜𝐚𝐬𝐞. my_string = "Hello" lower_case = my_string.lower()  # lower_case will be "hello" upper_case = my_string.upper()  # upper_case will be "HELLO" 𝟒- 𝐬𝐭𝐫𝐢𝐩(): 𝐑𝐞𝐦𝐨𝐯𝐞𝐬 𝐥𝐞𝐚𝐝𝐢𝐧𝐠 𝐚𝐧𝐝 𝐭𝐫𝐚𝐢𝐥𝐢𝐧𝐠 𝐰𝐡𝐢𝐭𝐞𝐬𝐩𝐚𝐜𝐞 𝐟𝐫𝐨𝐦 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠. my_string = "   Hello   " stripped_string = my_string.strip()  # stripped_string will be "Hello" 𝟓- 𝐬𝐩𝐥𝐢𝐭(): 𝐒𝐩𝐥𝐢𝐭𝐬 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠 𝐢𝐧𝐭𝐨 𝐚 𝐥𝐢𝐬𝐭 𝐨𝐟 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠𝐬 𝐛𝐚𝐬𝐞𝐝 𝐨𝐧 𝐚 𝐝𝐞𝐥𝐢𝐦𝐢𝐭𝐞𝐫. my_string = "apple,banana,orange" fruits = my_string.split(",")  # fruits will be ["apple", "banana", "orange"] 𝟔- 𝐣𝐨𝐢𝐧(): 𝐉𝐨𝐢𝐧𝐬 𝐭𝐡𝐞 𝐞𝐥𝐞𝐦𝐞𝐧𝐭𝐬 𝐨𝐟 𝐚 𝐥𝐢𝐬𝐭 𝐢𝐧𝐭𝐨 𝐚 𝐬𝐢𝐧𝐠𝐥𝐞 𝐬𝐭𝐫𝐢𝐧𝐠 𝐮𝐬𝐢𝐧𝐠 𝐚 𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐞𝐝 𝐬𝐞𝐩𝐚𝐫𝐚𝐭𝐨𝐫. fruits = ["apple", "banana", "orange"] my_string = ",".join(fruits)  # my_string will be "apple,banana,orange" 𝟕- 𝐟𝐢𝐧𝐝() 𝐚𝐧𝐝 𝐢𝐧𝐝𝐞𝐱(): 𝐒𝐞𝐚𝐫𝐜𝐡 𝐟𝐨𝐫 𝐚 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠 𝐰𝐢𝐭𝐡𝐢𝐧 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠 𝐚𝐧𝐝 𝐫𝐞𝐭𝐮𝐫𝐧 𝐢𝐭𝐬 𝐢𝐧𝐝𝐞𝐱. my_string = "Hello, world!" index1 = my_string.find("world")  # index1 will be 7 index2 = my_string.index("world")  # index2 will also be 7 𝟖- 𝐫𝐞𝐩𝐥𝐚𝐜𝐞(): 𝐑𝐞𝐩𝐥𝐚𝐜𝐞𝐬 𝐨𝐜𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐞𝐬 𝐨𝐟 𝐚 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐚𝐧𝐨𝐭𝐡𝐞𝐫 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠. my_string = "Hello, world!" new_string = my_string.replace("world", "Python")  # new_string will be "Hello, Python!" 𝟗- 𝐬𝐭𝐚𝐫𝐭𝐬𝐰𝐢𝐭𝐡() 𝐚𝐧𝐝 𝐞𝐧𝐝𝐬𝐰𝐢𝐭𝐡(): 𝐂𝐡𝐞𝐜𝐤𝐬 𝐢𝐟 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠 𝐬𝐭𝐚𝐫𝐭𝐬 𝐨𝐫 𝐞𝐧𝐝𝐬 𝐰𝐢𝐭𝐡 𝐚 𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐞𝐝 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠. my_string = "Hello, world!" starts_with_hello = my_string.startswith("Hello")  # True ends_with_world = my_string.endswith("world")  # False 𝟏𝟎- 𝐜𝐨𝐮𝐧𝐭(): 𝐂𝐨𝐮𝐧𝐭𝐬 𝐭𝐡𝐞 𝐨𝐜𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐞𝐬 𝐨𝐟 𝐚 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠 𝐢𝐧 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠. my_string = "apple, banana, orange, banana" count = my_string.count("banana")  # count will be 2 Python Complete Notion Notes with 5 Practical Projects 👇👇 https://topmate.io/analyst/871454 Hope you'll like it Like this post if you need more resources like this 👍❤️

Python Interview Questions & Answers ✅

🎡 5 Sites to Prepare for Tech Interviews 1. Leetcode 🔗 leetcode.com 2. Interviewing .io 🔗 interviewing.io 3. Coding Interview University 🔗 https://github.com/jwasham/coding-interview-university 4. JavaScript Algorithms 🔗 https://github.com/trekhleb/javascript-algorithms 5. JavaScript Questions 🔗 https://github.com/lydiahallie/javascript-questions

https://topmate.io/analyst/1024129 If you're a job seeker, these well structured document resources will help you to know and learn all the real time Data Science & Machine Learning Interview questions with their exact answer. folks who are having 0-4+ years of experience have cracked the interview using this guide! Please use the above link to avail them!👆 NOTE: -Most data aspirants hoard resources without actually opening them even once! The reason for keeping a small price for these resources is to ensure that you value the content available inside this and encourage you to make the best out of it. Hope this helps in your job search journey... All the best!👍✌️

Prepare for Success with PREPARO - Your AI-Powered Interview and Test Preparation Bot! Looking to ace your next interview or exam? Meet PREPARO, the AI service designed to help you get ahead with personalized practice sessions tailored to your needs. Features: - Interview Mode: Practice with 10 open-ended questions based on your job requirements. Respond with text or voice messages for a fully interactive experience. - Test Mode: Sharpen your knowledge with multiple-choice questions on any topic you choose. Each test includes 10 questions with 4 possible answers. - Roadmap Mode: Get a customized development path for your dream job. Just specify your desired role, and PREPARO will guide you through the necessary steps. - Personalized Practice: Get questions tailored to your specific job or test topic. - Interactive Feedback: Immediate responses to help you learn and improve. - Flexible Learning: Switch between text and voice responses for a more engaging experience. Whether you're preparing for a job interview, an important test, or planning your career path, PREPARO is here to help you succeed. Start practicing now and take your preparation to the next level. Try PREPARO

Data structures in Python - cheat sheet
+4
Data structures in Python - cheat sheet

https://topmate.io/analyst/907371 If you're a job seeker, these well structured document resources will help you to know and learn all the real time Python Interview questions with their exact answer. folks who are having 0-4+ years of experience have cracked the interview using this guide! Please use the above link to avail them!👆 NOTE: -Most data aspirants hoard resources without actually opening them even once! The reason for keeping a small price for these resources is to ensure that you value the content available inside this and encourage you to make the best out of it. Hope this helps in your job search journey... All the best!👍✌️

Pandas is a single-threaded library, utilizing only one CPU core. To achieve parallelism, Dask is required. In comparison, Po
Pandas is a single-threaded library, utilizing only one CPU core. To achieve parallelism, Dask is required. In comparison, Polars automatically uses available CPU cores without additional setup.

⌨️ 50 Python Interview Q/A 💥
+6
⌨️ 50 Python Interview Q/A 💥

⌨️ Prime Functions In Python
⌨️ Prime Functions In Python

Python Cheat Sheet.pdf17.29 MB

The Ultimate Guide to PYTHON CERTIFICATIONS.pdf9.66 KB

Python's map and filter functions are powerful tools. However, combining them can lead to complex nested calls. The Pipe libr
Python's map and filter functions are powerful tools. However, combining them can lead to complex nested calls. The Pipe library offers a more elegant solution with pipes, allowing for intuitive and readable operation chaining.

+1
Natural Language Processing with Transformers Lewis Tunstall, 2022