Python for Data Analysts
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Find top Python resources from global universities, cool projects, and learning materials for data analytics. For promotions: @coderfun Useful links: heylink.me/DataAnalytics
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Tarmoq:📈 Telegram kanali Python for Data Analysts analitikasi
Python for Data Analysts (@pythonanalyst) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 51 830 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 2 495-o'rinni va Hindiston mintaqasida 6 883-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 51 830 obunachiga ega bo‘ldi.
26 Avgust, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 118 ga, so‘nggi 24 soatda esa -5 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 4.34% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.00% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 248 marta ko‘riladi; birinchi sutkada odatda 519 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 8 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent visualization, panda, analyst, sql, analytic kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Find top Python resources from global universities, cool projects, and learning materials for data analytics.
For promotions: @coderfun
Useful links: heylink.me/DataAnalytics”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 27 Avgust, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
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Obunachilar
-524 soatlar
-297 kunlar
+11830 kunlar
Postlar arxiv
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𝟱 𝗙𝗥𝗘𝗘 𝗠𝗜𝗧 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗧𝗲𝗰𝗵, 𝗔𝗜 & 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲😍
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𝐋𝐢𝐧𝐤👇:-
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Your gateway to a smarter career✅️
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𝗠𝗮𝘀𝘁𝗲𝗿 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗳𝗼𝗿 𝗙𝗿𝗲𝗲 𝗶𝗻 𝟮𝟬𝟮𝟱!😍
Want to communicate with AI like a pro? 🤖
Whether you’re a data analyst, AI developer, content creator, or student, this is the must-have skill of 2025✨️
𝐋𝐢𝐧𝐤👇:-
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Save this now & unlock your AI potential!⚡
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10 SQL Concepts Every Data Analyst Should Master 👇
✅ SELECT, WHERE, ORDER BY – Core of querying your data
✅ JOINs (INNER, LEFT, RIGHT, FULL) – Combine data from multiple tables
✅ GROUP BY & HAVING – Aggregate and filter grouped data
✅ Subqueries – Nest queries inside queries for complex logic
✅ CTEs (Common Table Expressions) – Write cleaner, reusable SQL logic
✅ Window Functions – Perform advanced analytics like rankings & running totals
✅ Indexes – Boost your query performance
✅ Normalization – Structure your database efficiently
✅ UNION vs UNION ALL – Combine result sets with or without duplicates
✅ Stored Procedures & Functions – Reusable logic inside your DB
React with ❤️ if you want me to cover each topic in detail
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
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Almost everyone knows that these are the tools a Data Analyst works with:
➡️ SQL
➡️ Excel
➡️ Power BI/Tableau
➡️ Python
But people getting started with analytics are confused about the preferences of picking these tools.
There are various kinds of data analytics roles available in the market :
➡️ BI + SQL: Will primarily be involved in BI development.
➡️ SQL + Excel: Will primarily work on Excel reporting.
➡️ SQL + Python: Will primarily do data analysis using python.
Now, If you are getting started with learning analytics, choose any one role that interests you the most and focus on completing the primary tools that the role requires. Learn them VERY WELL.
Learn any of the above combinations that interests you first and then start looking out for opportunities which ask for these primary tools and simultaneously start learning the basics of the 3rd tool.
You don't have to focus on being good with each and every tool but being good with any of the above combinations always works.
Join this channel to learn everything about Data Analytics 👇
https://t.me/sqlspecialist
Hope this helps you 😊
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SQL Interview Questions
1. How would you find duplicate records in SQL?
2.What are various types of SQL joins?
3.What is a trigger in SQL?
4.What are different DDL,DML commands in SQL?
5.What is difference between Delete, Drop and Truncate?
6.What is difference between Union and Union all?
7.Which command give Unique values?
8. What is the difference between Where and Having Clause?
9.Give the execution of keywords in SQL?
10. What is difference between IN and BETWEEN Operator?
11. What is primary and Foreign key?
12. What is an aggregate Functions?
13. What is the difference between Rank and Dense Rank?
14. List the ACID Properties and explain what they are?
15. What is the difference between % and _ in like operator?
16. What does CTE stands for?
17. What is database?what is DBMS?What is RDMS?
18.What is Alias in SQL?
19. What is Normalisation?Describe various form?
20. How do you sort the results of a query?
21. Explain the types of Window functions?
22. What is limit and offset?
23. What is candidate key?
24. Describe various types of Alter command?
25. What is Cartesian product?
Like this post if you need more content like this ❤️
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𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍
𝗦𝗤𝗟:- https://pdlink.in/3TcvfsA
𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲:- https://pdlink.in/3Hfpwjc
𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝗰𝗲:- https://pdlink.in/3ZyQpFd
𝗣𝘆𝘁𝗵𝗼𝗻 :- https://pdlink.in/3Hnx3wh
𝗗𝗲𝘃𝗢𝗽𝘀 :- https://pdlink.in/4jyxBwS
𝗪𝗲𝗯 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 :- https://pdlink.in/4jCAtJ5
Enroll for FREE & Get Certified 🎓
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Career Path for a Data Analyst
Education: Start by earning a bachelor's degree in fields like math, stats, economics, or computer science.
Skills Growth: Learn programming (Python/R), data tools (SQL/Excel), and visualization. Master data analysis basics.
Entry-Level Role: Begin as a Junior Data Analyst. Learn data cleaning, organization, and basic analysis.
Specialization: Deepen your expertise in a specific industry. Explore advanced analytics and visualization tools.
Advanced Analytics: Move up to Senior Data Analyst. Tackle complex projects and predictive modeling.
Machine Learning: Explore machine learning and data modeling techniques. Familiarize yourself with algorithms, and learn how to implement predictive and classification models.
Domain Expertise: Develop expertise in a particular industry, such as healthcare, finance, e-commerce, etc. This knowledge will enable you to provide more valuable insights from data.
Leadership Roles: As you gain experience, you can move into roles like Data Analytics Manager or Data Science Manager, where you'll oversee teams and projects.
Continuous Learning: Stay updated with the latest tools, techniques, and industry trends. Attend workshops, conferences, and online courses to keep your skills relevant.
Networking: Build a strong professional network within the data analytics community. This can open up opportunities and help you stay informed about industry developments.
Remember, your career path can be personalized based on your interests and strengths. Continuous learning and adaptability are key in the ever-evolving field of data analysis :)
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WhatsApp is no longer a platform just for chat.
It's an educational goldmine.
If you do, you’re sleeping on a goldmine of knowledge and community. WhatsApp channels are a great way to practice data science, make your own community, and find accountability partners.
I have curated the list of best WhatsApp channels to learn coding & data science for FREE
Free Courses with Certificate
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Jobs & Internship Opportunities
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https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226
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Python Free Books & Projects
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Java Free Resources
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Coding Interviews
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https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
SQL For Data Analysis
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https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
Power BI Resources
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Programming Free Resources
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https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17
Data Science Projects
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Learn Data Science & Machine Learning
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Excel for Data Analyst
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ENJOY LEARNING 👍👍
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𝗦𝗤𝗟 𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍
Looking to master SQL for Data Analytics or prep for your dream tech job? 💼
These 3 Free SQL resources will help you go from beginner to job-ready—without spending a single rupee! 📊✨
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/3TcvfsA
💥 Start learning today and build the skills top companies want!✅️
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Python for Data Analytics - Quick Cheatsheet with Cod e Example 🚀
1️⃣ Data Manipulation with Pandas
import pandas as pd
df = pd.read_csv("data.csv")
df.to_excel("output.xlsx")
df.head()
df.info()
df.describe()
df[df["sales"] > 1000]
df[["name", "price"]]
df.fillna(0, inplace=True)
df.dropna(inplace=True) import numpy as np
arr = np.array([1, 2, 3, 4])
print(arr.shape)
np.mean(arr)
np.median(arr)
np.std(arr) import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4], [10, 20, 30, 40])
plt.bar(["A", "B", "C"], [5, 15, 25])
plt.show()
import seaborn as sns
sns.heatmap(df.corr(), annot=True)
sns.boxplot(x="category", y="sales", data=df)
plt.show() df.isnull().sum()
df.corr()
sns.histplot(df["sales"], bins=30)
sns.boxplot(y=df["price"]) import sqlite3
conn = sqlite3.connect("database.db")
df = pd.read_sql("SELECT * FROM sales", conn)
conn.close()
cursor = conn.cursor()
cursor.execute("SELECT AVG(price) FROM products")
result = cursor.fetchone()
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𝗔𝗱𝗱 𝗗𝗲𝗹𝗼𝗶𝘁𝘁𝗲 𝘁𝗼 𝗬𝗼𝘂𝗿 𝗥𝗲𝘀𝘂𝗺𝗲 — 𝗡𝗼 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗡𝗲𝗲𝗱𝗲𝗱!😍
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Now you can — thanks to this free Deloitte virtual internship, open to everyone!👨💻📌
𝐋𝐢𝐧𝐤👇:-
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All 100% online, self-paced, and with a certificate of completion you can proudly share on LinkedIn and your resume📝✅️
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🚀 Essential Python snippets to explore data:
1. .head() - Review top rows
2. .tail() - Review bottom rows
3. .info() - Summary of DataFrame
4. .shape - Shape of DataFrame
5. .describe() - Descriptive stats
6. .isnull().sum() - Check missing values
7. .dtypes - Data types of columns
8. .unique() - Unique values in a column
9. .nunique() - Count unique values
10. .value_counts() - Value counts in a column
11. .corr() - Correlation matrix
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Free Resources for Python
Codebasics python tutorials (first 16) —
https://www.youtube.com/playlist?list=PLeo1K3hjS3uv5U-Lmlnucd7gqF-3ehIh0
Practice Python course
https://dabeaz-course.github.io/practical-python/Notes/Contents.html
Codebasics python HINDI tutorials —
https://www.youtube.com/playlist?list=PLPbgcxheSpE1DJKfdko58_AIZRIT0TjpO
Useful Python resources for beginners
https://t.me/programming_guide/8
Python 3 Book for beginners
https://t.me/pythondevelopersindia/272?single
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🎓 𝗟𝗲𝗮𝗿𝗻 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗳𝗼𝗿 𝗙𝗿𝗲𝗲 𝗳𝗿𝗼𝗺 𝗛𝗮𝗿𝘃𝗮𝗿𝗱, 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱, 𝗠𝗜𝗧 & 𝗚𝗼𝗼𝗴𝗹𝗲😍
Why pay thousands when you can access world-class Computer Science courses for free? 🌐
Top institutions like Harvard, Stanford, MIT, and Google offer high-quality learning resources to help you master in-demand tech skills👨🎓📌
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/3ZyQpFd
Perfect for students, self-learners, and career switchers✅️
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7 Must-Have Tools for Data Analysts in 2025:
✅ SQL – Still the #1 skill for querying and managing structured data
✅ Excel / Google Sheets – Quick analysis, pivot tables, and essential calculations
✅ Python (Pandas, NumPy) – For deep data manipulation and automation
✅ Power BI – Transform data into interactive dashboards
✅ Tableau – Visualize data patterns and trends with ease
✅ Jupyter Notebook – Document, code, and visualize all in one place
✅ Looker Studio – A free and sleek way to create shareable reports with live data.
Perfect blend of code, visuals, and storytelling.
React with ❤️ for free tutorials on each tool
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
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𝟱 𝗠𝘂𝘀𝘁-𝗙𝗼𝗹𝗹𝗼𝘄 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗖𝗵𝗮𝗻𝗻𝗲𝗹𝘀 𝗳𝗼𝗿 𝗔𝘀𝗽𝗶𝗿𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 𝗶𝗻 𝟮𝟬𝟮𝟱😍
Want to Become a Data Scientist in 2025? Start Here!🎯
If you’re serious about becoming a Data Scientist in 2025, the learning doesn’t have to be expensive — or boring!🚀
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4kfBR5q
Perfect for beginners and aspiring pros✅️
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Lists 🆚 Tuples 🆚 Dictionaries
What's the difference?
Lists are mutable.
Tuples are immutable.
Dictionaries are associative.
When should you use each?
Lists:
⟶ When you want to add or remove elements
⟶ When you want to sort elements
⟶ When you want to slice elements
Tuples:
⟶ When you want a constant object
⟶ When you want to send multiple in a function
⟶ When you want to return multiple from a function
Dictionaries:
⟶ When you want to map keys to values
⟶ When you want to loop over the keys
⟶ When you want to validate if key exists
Now, pick your weapon of mass data analysis and become a Python pro!
Python Interview Q&A: https://topmate.io/coding/898340
Like for more ❤️
ENJOY LEARNING 👍👍
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𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲 𝗼𝗻 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗯𝘆 𝗗𝗲𝗲𝗽𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴.𝗔𝗜 & 𝗢𝗽𝗲𝗻𝗔𝗜😍
💡 Think ChatGPT is Just for Fun? Think Again📌
In today’s AI-driven world, knowing how to communicate effectively with large language models (LLMs) is more than just a bonus — it’s a competitive edge📊🎯
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4jn7aKh
Use ChatGPT like a developer — not just a casual user✅️
