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Learn python🔥

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📈 Telegram kanali Python learning analitikasi

Python learning (@python3learning) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 23 459 obunachidan iborat bo'lib, Taʼlim toifasida 8 467-o'rinni va Hindiston mintaqasida 18 299-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 23 459 obunachiga ega bo‘ldi.

23 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -304 ga, so‘nggi 24 soatda esa -14 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 4.70% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining N/A% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 1 102 marta ko‘riladi; birinchi sutkada odatda 0 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 2 ta reaksiya keladi.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
Learn python🔥

Yuqori yangilanish chastotasi (oxirgi ma’lumot 24 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

23 459
Obunachilar
-1424 soatlar
-687 kunlar
-30430 kunlar
Postlar arxiv
🐍 Python 3.15 Changed More Than I Expected I've been writing Python for years, and this release surprised me. 🔥 Faster performance 🔥 Better error messages 🔥 Cleaner syntax improvements 🔥 Developer experience upgrades Most developers haven't noticed these changes yet. https://medium.com/@vaishnavi.singh0324/python-3-15-changed-more-than-i-expected-and-ive-been-writing-python-for-8-years-a10af41bc6e4

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📊 Software/ IT Career Guidance Masterclass LEARN: ✅ A proven 90-day job preparation roadmap ✅ How top product companies hire ✅ Strategies for both Tech & Non-Tech roles ✅ Interview preparation & career growth insights Time: 11 June 2026, 7:00 PM Eligiblity • Working Professionals (IT & Non-IT) • Job Seekers & Career Switchers Register for FREE https://rebrand.ly/Free-IT-Career-Guidance26 ⚡ Limited Slots Available

I Built an AI Agent in Python in Under 30 Minutes — Here’s Exactly How 👇 https://medium.com/ai-in-plain-english/i-built-an-a
I Built an AI Agent in Python in Under 30 Minutes — Here’s Exactly How 👇 https://medium.com/ai-in-plain-english/i-built-an-ai-agent-in-python-in-under-30-minutes-heres-exactly-how-61196d2ab097

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🚀 Python Developers, This Changes Everything! uv is replacing pip, venv, and even Poetry ⚡ Super fast package installs, virt
🚀 Python Developers, This Changes Everything! uv is replacing pip, venv, and even Poetry ⚡ Super fast package installs, virtual environments, and dependency management — all in ONE tool. ✅ 100x Faster Installs ✅ Simple Commands ✅ Better Developer Experience ✅ Perfect for Python Beginners & Pros I wrote a detailed Medium article explaining everything in easy words 👇 👉 https://medium.com/@atharvjaiswal56/uv-replaced-pip-venv-and-poetry-100x-faster-installs-b6e8b2a35a1d If you enjoy Python, AI & Dev content, follow me on Medium ❤️

*FREE Data Analytics Workshop – Power BI & Tableau* 📅 18 March 2026 ⏰ 7:00 PM | 90 Minutes 🌐 Language: English Learn how to
*FREE Data Analytics Workshop – Power BI & Tableau* 📅 18 March 2026 ⏰ 7:00 PM | 90 Minutes 🌐 Language: English Learn how to convert raw data into powerful dashboards using Power BI & Tableau. 📊 Eligibilty: Freshers & Working Professionals 📌 Register Now : https://link.guvi.in/pythonlearning03022 Limited Seats 🤳🏼 Hurry up

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Python Projects with Source Code for Final Year FREE SOURCE CODE LINK 🔗 Yearhttps://inprogrammer.com/python-projects-with-source-code-for-final-year/

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Repost from N/a
Top 50 Data Analyst Interview Questions (2025) 🎯📊 1. What does a data analyst do? 2. Difference between data analyst, data scientist, and data engineer. 3. What are the key skills every data analyst must have? 4. Explain the data analysis process. 5. What is data wrangling or data cleaning? 6. How do you handle missing values? 7. What is the difference between structured and unstructured data? 8. How do you remove duplicates in a dataset? 9. What are the most common data types in Python or SQL? 10. What is the difference between INNER JOIN and LEFT JOIN? 11. Explain the concept of normalization in databases. 12. What are measures of central tendency? 13. What is standard deviation and why is it important? 14. Difference between variance and covariance. 15. What are outliers and how do you treat them? 16. What is hypothesis testing? 17. Explain p-value in simple terms. 18. What is correlation vs. causation? 19. How do you explain insights from a dashboard to non-technical stakeholders? 20. What tools do you use for data visualization? 21. Difference between Tableau and Power BI. 22. What is a pivot table? 23. How do you build a dashboard from scratch? 49. What do you do if data contradicts business intuition? 50. What are your favorite analytics tools and why? 🎓 Data Analyst Jobs: https://whatsapp.com/channel/0029Vb6r6218kyyQgBDNjm26 💬 Tap ❤️ for the detailed answers!

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*** ✅ *Python Logic Building Interview Question* 🧠🐍 You have a list of numbers:
nums = [3, 5, 7, 9, 12, 17, 20, 21]
*Question:* Find and print all numbers in the list that are prime. *Expected Output:*
[3, 5, 7, 17]
*Python Code:*
def is_prime(n):
    if n < 2:
        return False
    for i in range(2, int(n**0.5) + 1):
        if n % i == 0:
            return False
    return True

prime_nums = [n for n in nums if is_prime(n)]
print(prime_nums)
*Explanation:* – Checks each number with is_prime() logic – Uses list comprehension for concise filtering – Prints list of all prime numbers 💬 *Tap ❤️ for more logic-building questions!*

✅ *Python Scenario-Based Interview Question* 🧠🐍 You have a list:
numbers = [1, 2, 3, 2, 4, 1, 5, 2]
*Question:* Find the number that appears most frequently in the list. *Expected Output:*
2
*Python Code:*
from collections import Counter

most_common_num = Counter(numbers).most_common(1)[0][0]
print(most_common_num)
*Explanation:* – Counter() counts occurrences of each element – most_common(1) returns the most frequent item – Access [0][0] to get just the number 💬 *Tap ❤️ for more bite-sized Python tips!* *** Would you like the next one to be slightly more advanced (e.g., involving strings or list comprehensions)?