Python for Data Analysts
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Find top Python resources from global universities, cool projects, and learning materials for data analytics.

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Useful links: heylink.me/DataAnalytics
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DSA in Python ๐Ÿ‘†๐Ÿ‘†
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Useful Pandas Functions ๐Ÿ‘†
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๐—ง๐—ผ๐—ฝ ๐—ฃ๐˜†๐˜๐—ต๐—ผ๐—ป ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ค๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—”๐˜€๐—ธ๐—ฒ๐—ฑ ๐—ฏ๐˜† ๐— ๐—ก๐—–๐˜€๐Ÿ˜

If you can answer these Python questions, youโ€™re already ahead of 90% of candidates.๐Ÿง‘โ€๐Ÿ’ปโœจ๏ธ

These arenโ€™t your average textbook questions. These are real interview questions asked in top MNCs โ€” designed to test how deeply you understand Python.๐Ÿ“Š๐Ÿ“

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/4mu4oVx

This is the smart way to prepareโœ…๏ธ
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DATA ANALYST Interview Questions (0-3 yr) (SQL, Power BI)

๐Ÿ‘‰ Power BI:

Q1: Explain step-by-step how you will create a sales dashboard from scratch.

Q2: Explain how you can optimize a slow Power BI report.

Q3: Explain Any 5 Chart Types and Their Uses in Representing Different Aspects of Data.

๐Ÿ‘‰SQL:

Q1: Explain the difference between RANK(), DENSE_RANK(), and ROW_NUMBER() functions using example.

Q2 โ€“ Q4 use Table: employee (EmpID, ManagerID, JoinDate, Dept, Salary)

Q2: Find the nth highest salary from the Employee table.

Q3: You have an employee table with employee ID and manager ID. Find all employees under a specific manager, including their subordinates at any level.

Q4: Write a query to find the cumulative salary of employees department-wise, who have joined the company in the last 30 days.

Q5: Find the top 2 customers with the highest order amount for each product category, handling ties appropriately. Table: Customer (CustomerID, ProductCategory, OrderAmount)

๐Ÿ‘‰Behavioral:

Q1: Why do you want to become a data analyst and why did you apply to this company?

Q2: Describe a time when you had to manage a difficult task with tight deadlines. How did you handle it?

I have curated best top-notch Data Analytics Resources ๐Ÿ‘‡๐Ÿ‘‡
https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02

Hope this helps you ๐Ÿ˜Š
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Data analysis with Python Important Topics ๐Ÿ˜„โค๏ธ
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Data Wrangling with Pandas Cheatsheet
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๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ ๐—ฆ๐—ค๐—Ÿ ๐—ถ๐—ป ๐—๐˜‚๐˜€๐˜ ๐Ÿณ ๐——๐—ฎ๐˜†๐˜€: ๐—ง๐—ต๐—ฒ ๐—จ๐—น๐˜๐—ถ๐—บ๐—ฎ๐˜๐—ฒ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—ฅ๐—ผ๐—ฎ๐—ฑ๐—บ๐—ฎ๐—ฝ ๐˜๐—ผ ๐—š๐—ฒ๐˜ ๐—๐—ผ๐—ฏ-๐—ฅ๐—ฒ๐—ฎ๐—ฑ๐˜†๐Ÿ˜

Want to learn SQL in just 7 days?๐Ÿง‘โ€๐ŸŽ“

Whether youโ€™re a complete beginner or prepping for interviews, this 7-day plan will take you from writing your first SELECT query to mastering JOINs, transactions, and even database design.๐Ÿง‘โ€๐Ÿ’ปโœจ๏ธ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/3Hs7Fps

Perfect for students, freshers, and aspiring data analysts.โœ…๏ธ
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30 Days Python Roadmap for Data Analysts ๐Ÿ‘†
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