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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

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📈 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 28 836 名订阅者,在 技术与应用 类别中位列第 4 615,并在 印度 地区排名第 14 432

📊 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 28 836 名订阅者。

根据 26 七月, 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 78,过去 24 小时变化为 -1,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 2.43%。内容发布后 24 小时内通常能获得 0.57% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 701 次浏览,首日通常累积 163 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 2
  • 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 27 七月, 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。

28 836
订阅者
-124 小时
+417
+7830
帖子存档
To be GOOD in Data Science you need to learn: - Python - SQL - PowerBI To be GREAT in Data Science you need to add: - Business Understanding - Knowledge of Cloud - Many-many projects But to LAND a job in Data Science you need to prove you can: - Learn new things - Communicate clearly - Solve problems #datascience

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Quick Python Cheat Sheet for Beginners 🐍✍️ Python is widely used for data analysis, automation, and AI—perfect for beginners starting their coding journey. Aggregation Functions 📊 • sum(list) → Adds all values 👉 sum([1,2,3]) = 6 • len(list) → Counts total elements 👉 len([1,2,3]) = 3 • max(list) → Highest value 👉 max([4,7,2]) = 7 • min(list) → Lowest value 👉 min([4,7,2]) = 2 • sum(list)/len(list) → Average 👉 sum([10,20])/2 = 15 Lookup / Searching 🔍 • in → Check existence 👉 5 in [1,2,5] = True • list.index(value) → Position of value 👉 [10,20,30].index(20) = 1 • Dictionary lookup 👉 data = {"name": "John", "age": 25} data["name"] # John Logical Operations 🧠 • if condition: → Decision making 👉 if x > 10: print("High") else: print("Low") • and → All conditions true • or → Any condition true • not → Reverse condition Text (String) Functions 🔤 • len(text) → Length 👉 len("hello") = 5 • text.lower() → Lowercase • text.upper() → Uppercase • text.strip() → Remove spaces 👉 " hi ".strip() = "hi" • text.replace(old, new) 👉 "hi".replace("h","H") = "Hi" • String concatenation 👉 "Hello " + "World" Date Time Functions 📅 • from datetime import datetime • datetime.now() → Current date time • Extract values: now = datetime.now() now.year now.month now.day Math Functions ➗ • import math • math.sqrt(x) → Square root • math.ceil(x) → Round up • math.floor(x) → Round down • abs(x) → Absolute value Conditional Aggregation (Like Excel SUMIF) ⚡ • Using list comprehension nums = [10, 20, 30, 40] sum(x for x in nums if x > 20) # 70 • Count condition len([x for x in nums if x > 20]) # 2 Pro Tip for Data Analysts 💡 👉 For real-world work, use libraries: pandas & numpy Example: import pandas as pd df["salary"].mean() Python Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L Double Tap ♥️ For More

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🔰 Python Set Methods
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🔰 Python Set Methods

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Top linked list questions to practice: 1. 🔄 Reverse a Linked List 2. 🔁 Detect a Cycle in a Linked List 3. 🤝 Find the Merge Point of Two Linked Lists 4. 🚫 Remove N-th Node From End of List 5. 🔗 Merge Two Sorted Linked Lists 6. 🖼️ Check if a Linked List is a Palindrome 7. 🚨 Remove Duplicates from a Sorted List 8. 🎯 Find the Middle of a Linked List 9. 🔄 Rotate a Linked List 10. 📑 Implement a Doubly Linked List 11. 📊 Implement a Circular Linked List 12. 🛠️ Add Two Numbers Represented by Linked Lists 13. 🧹 Remove Linked List Elements 14. 🧩 Partition List around a value 15. 🔄 Reverse Nodes in k-Group

🔰 Take Screenshots using Python
🔰 Take Screenshots using Python

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