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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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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๐Ÿ“ ๐…๐ซ๐ž๐ž ๐˜๐จ๐ฎ๐“๐ฎ๐›๐ž ๐‘๐ž๐ฌ๐จ๐ฎ๐ซ๐œ๐ž๐ฌ ๐ญ๐จ ๐๐ฎ๐ข๐ฅ๐ ๐€๐ˆ ๐€๐ฎ๐ญ๐จ๐ฆ๐š๐ญ๐ข๐จ๐ง๐ฌ & ๐€๐ ๐ž๐ง๐ญ๐ฌ ๐–๐ข๐ญ๐ก๐จ๐ฎ๐ญ ๐‚๐จ๐๐ข๐ง๐ ๐Ÿ˜

Want to Create AI Automations & Agents Without Writing a Single Line of Code?๐Ÿง‘โ€๐Ÿ’ป

These 5 free YouTube tutorials will take you from complete beginner to automation expert in record time.๐Ÿง‘โ€๐ŸŽ“โœจ๏ธ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/4lhYwhn

Just pure, actionable automation skills โ€” for free.โœ…๏ธ
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Quick Recap of Power BI Concepts

1๏ธโƒฃ Power Query: The data transformation engine that lets you clean, reshape, and combine data before loading it into Power BI.

2๏ธโƒฃ Data Model: A structure of tables, relationships, and calculated fields that supports report creation.

3๏ธโƒฃ Relationships: Connections between tables that allow you to create reports using data from multiple tables.

4๏ธโƒฃ DAX (Data Analysis Expressions): A formula language used for creating calculated columns, measures, and custom tables.

5๏ธโƒฃ Visualizations: Graphical representations of data, such as bar charts, line charts, maps, and tables.

6๏ธโƒฃ Slicers: Interactive filters added to reports to help users refine data views.

7๏ธโƒฃ Measures: Calculations created using DAX that perform dynamic aggregations based on the context in your report.

8๏ธโƒฃ Calculated Columns: Static columns created using DAX expressions that perform row-by-row calculations.

9๏ธโƒฃ Reports: A collection of visualizations, text, and slicers that tell a story using your data.

๐Ÿ”Ÿ Power BI Service: The online platform where you publish, share, and collaborate on Power BI reports and dashboards.

I have curated the best interview resources to crack Power BI Interviews ๐Ÿ‘‡๐Ÿ‘‡
https://t.iss.one/DataSimplifier

Hope you'll like it

Like this post if you need more content like this ๐Ÿ‘โค๏ธ

Share with credits: https://t.iss.one/sqlspecialist

Hope it helps :)
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