📊 Pandas Interview Question (Frequently Asked!)
❓ Interviewers love to ask this:
“Your dataset has duplicate records. How will you handle them in Pandas?”
✅ Answer:
➡️ Use df.duplicated() to identify duplicate rows.
➡️ Use df.drop_duplicates() to remove them cleanly.
➡️ You can also target specific columns using the subset parameter.
👍 React if you want more frequently asked Pandas, SQL, PowerBI interview questions for Data Analyst roles!
❓ Interviewers love to ask this:
“Your dataset has duplicate records. How will you handle them in Pandas?”
✅ Answer:
➡️ Use df.duplicated() to identify duplicate rows.
➡️ Use df.drop_duplicates() to remove them cleanly.
➡️ You can also target specific columns using the subset parameter.
👍 React if you want more frequently asked Pandas, SQL, PowerBI interview questions for Data Analyst roles!
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* Learn from India's Best Mentors
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1. Danny’s Diner:
Restaurant analytics to understand the customer orders pattern.
Link: https://8weeksqlchallenge.com/case-study-1/
2. Pizza Runner
Pizza shop analytics to optimize the efficiency of the operation
Link: https://8weeksqlchallenge.com/case-study-2/
3. Foodie Fie
Subnoscription-based food content platform
Link: https://lnkd.in/gzB39qAT
4. Data Bank: That’s money
Analytics based on customer activities with the digital bank
Link: https://lnkd.in/gH8pKPyv
5. Data Mart: Fresh is Best
Analytics on Online supermarket
Link: https://lnkd.in/gC5bkcDf
6. Clique Bait: Attention capturing
Analytics on the seafood industry
Link: https://lnkd.in/ggP4JiYG
7. Balanced Tree: Clothing Company
Analytics on the sales performance of clothing store
Link: https://8weeksqlchallenge.com/case-study-7
8. Fresh segments: Extract maximum value
Analytics on online advertising
Link: https://8weeksqlchallenge.com/case-study-8
Join for more: https://news.1rj.ru/str/sqlanalyst
1. Danny’s Diner:
Restaurant analytics to understand the customer orders pattern.
Link: https://8weeksqlchallenge.com/case-study-1/
2. Pizza Runner
Pizza shop analytics to optimize the efficiency of the operation
Link: https://8weeksqlchallenge.com/case-study-2/
3. Foodie Fie
Subnoscription-based food content platform
Link: https://lnkd.in/gzB39qAT
4. Data Bank: That’s money
Analytics based on customer activities with the digital bank
Link: https://lnkd.in/gH8pKPyv
5. Data Mart: Fresh is Best
Analytics on Online supermarket
Link: https://lnkd.in/gC5bkcDf
6. Clique Bait: Attention capturing
Analytics on the seafood industry
Link: https://lnkd.in/ggP4JiYG
7. Balanced Tree: Clothing Company
Analytics on the sales performance of clothing store
Link: https://8weeksqlchallenge.com/case-study-7
8. Fresh segments: Extract maximum value
Analytics on online advertising
Link: https://8weeksqlchallenge.com/case-study-8
❤3
📊 Pandas Interview Question (Frequently Asked!)
❓ Interviewers love to ask this:
“Your dataset has duplicate records. How will you handle them in Pandas?”
✅ Answer:
➡️ Use df.duplicated() to identify duplicate rows.
➡️ Use df.drop_duplicates() to remove them cleanly.
➡️ You can also target specific columns using the subset parameter.
👍 React if you want more frequently asked Pandas, SQL, PowerBI interview questions for Data Analyst roles!
❓ Interviewers love to ask this:
“Your dataset has duplicate records. How will you handle them in Pandas?”
✅ Answer:
➡️ Use df.duplicated() to identify duplicate rows.
➡️ Use df.drop_duplicates() to remove them cleanly.
➡️ You can also target specific columns using the subset parameter.
👍 React if you want more frequently asked Pandas, SQL, PowerBI interview questions for Data Analyst roles!
❤6
📌 SQL Interview Question (Must-Know)
Question:
You have a table orders with the following columns:
order_id, customer_id, order_date, order_amount
👉 Write an SQL query to find the total order amount for each customer who has placed more than 3 orders.
✅ Solution:
SELECT
customer_id,
SUM(order_amount) AS total_order_amount
FROM orders
GROUP BY customer_id
HAVING COUNT(order_id) > 3;
🧠 Explanation:
GROUP BY customer_id → groups orders per customer
SUM(order_amount) → calculates total spending
HAVING COUNT(order_id) > 3 → filters customers with more than 3 orders
👍 React with 🔥 or 👍 if this helped
📊 Want more SQL interview questions & real-world scenarios? React and stay tuned!
Question:
You have a table orders with the following columns:
order_id, customer_id, order_date, order_amount
👉 Write an SQL query to find the total order amount for each customer who has placed more than 3 orders.
✅ Solution:
SELECT
customer_id,
SUM(order_amount) AS total_order_amount
FROM orders
GROUP BY customer_id
HAVING COUNT(order_id) > 3;
🧠 Explanation:
GROUP BY customer_id → groups orders per customer
SUM(order_amount) → calculates total spending
HAVING COUNT(order_id) > 3 → filters customers with more than 3 orders
👍 React with 🔥 or 👍 if this helped
📊 Want more SQL interview questions & real-world scenarios? React and stay tuned!
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✅ Open to everyone
✅ 100% Online | 6 Months
✅ Industry-ready curriculum
✅ Taught By IIT Roorkee Professors
🔥 Companies are actively hiring candidates with Data Science & AI skills.
⏳ Deadline: 31st January 2026
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✅ Top 10 Excel Interview Questions & Answers 📊💼
1️⃣ What is Excel and why is it used?
Excel is a spreadsheet program used for organizing, analyzing, and storing data in tabular form. It's widely used for data analysis, reporting, and financial modeling.
2️⃣ Key Excel components?
- Ribbon: Main menu
- Worksheet: A single sheet
- Workbook: A collection of worksheets
- Cell: Intersection of a row and column
3️⃣ What are Excel Functions?
Predefined formulas that perform specific calculations (e.g., SUM, AVERAGE, IF, VLOOKUP).
4️⃣ VLOOKUP vs. INDEX/MATCH?
- VLOOKUP: Searches for a value in the first column and returns a corresponding value.
- INDEX/MATCH: More flexible and overcomes VLOOKUP limitations, better for larger datasets.
5️⃣ What are Pivot Tables?
Interactive tables that summarize and analyze large datasets, allowing you to easily rearrange and filter data.
6️⃣ Conditional Formatting?
Applies formatting (e.g., colors, icons) to cells based on specific criteria, making it easier to identify trends and outliers.
7️⃣ How to remove duplicates?
Use the "Remove Duplicates" feature in the Data tab to eliminate redundant rows based on selected columns.
8️⃣ What are Excel Charts?
Visual representations of data (e.g., bar charts, line charts, pie charts) that help communicate trends and insights.
9️⃣ How to protect a worksheet?
Use the "Protect Sheet" feature in the Review tab to prevent unauthorized changes to the worksheet structure and content.
🔟 What are Macros?
Automated sequences of commands that can be recorded and replayed to perform repetitive tasks efficiently.
👍 React ❤️ if you found this helpful!
1️⃣ What is Excel and why is it used?
Excel is a spreadsheet program used for organizing, analyzing, and storing data in tabular form. It's widely used for data analysis, reporting, and financial modeling.
2️⃣ Key Excel components?
- Ribbon: Main menu
- Worksheet: A single sheet
- Workbook: A collection of worksheets
- Cell: Intersection of a row and column
3️⃣ What are Excel Functions?
Predefined formulas that perform specific calculations (e.g., SUM, AVERAGE, IF, VLOOKUP).
4️⃣ VLOOKUP vs. INDEX/MATCH?
- VLOOKUP: Searches for a value in the first column and returns a corresponding value.
- INDEX/MATCH: More flexible and overcomes VLOOKUP limitations, better for larger datasets.
5️⃣ What are Pivot Tables?
Interactive tables that summarize and analyze large datasets, allowing you to easily rearrange and filter data.
6️⃣ Conditional Formatting?
Applies formatting (e.g., colors, icons) to cells based on specific criteria, making it easier to identify trends and outliers.
7️⃣ How to remove duplicates?
Use the "Remove Duplicates" feature in the Data tab to eliminate redundant rows based on selected columns.
8️⃣ What are Excel Charts?
Visual representations of data (e.g., bar charts, line charts, pie charts) that help communicate trends and insights.
9️⃣ How to protect a worksheet?
Use the "Protect Sheet" feature in the Review tab to prevent unauthorized changes to the worksheet structure and content.
🔟 What are Macros?
Automated sequences of commands that can be recorded and replayed to perform repetitive tasks efficiently.
👍 React ❤️ if you found this helpful!
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📈 Want to Excel at Data Analytics? Master These Essential Skills! ☑️
Core Concepts:
• Statistics & Probability – Understand distributions, hypothesis testing
• Excel – Pivot tables, formulas, dashboards
Programming:
• Python – NumPy, Pandas, Matplotlib, Seaborn
• R – Data analysis & visualization
• SQL – Joins, filtering, aggregation
Data Cleaning & Wrangling:
• Handle missing values, duplicates
• Normalize and transform data
Visualization:
• Power BI, Tableau – Dashboards
• Plotly, Seaborn – Python visualizations
• Data Storytelling – Present insights clearly
Advanced Analytics:
• Regression, Classification, Clustering
• Time Series Forecasting
• A/B Testing & Hypothesis Testing
ETL & Automation:
• Web Scraping – BeautifulSoup, Scrapy
• APIs – Fetch and process real-world data
• Build ETL Pipelines
Tools & Deployment:
• Jupyter Notebook / Colab
• Git & GitHub
• Cloud Platforms – AWS, GCP, Azure
• Google BigQuery, Snowflake
Hope it helps :)
Core Concepts:
• Statistics & Probability – Understand distributions, hypothesis testing
• Excel – Pivot tables, formulas, dashboards
Programming:
• Python – NumPy, Pandas, Matplotlib, Seaborn
• R – Data analysis & visualization
• SQL – Joins, filtering, aggregation
Data Cleaning & Wrangling:
• Handle missing values, duplicates
• Normalize and transform data
Visualization:
• Power BI, Tableau – Dashboards
• Plotly, Seaborn – Python visualizations
• Data Storytelling – Present insights clearly
Advanced Analytics:
• Regression, Classification, Clustering
• Time Series Forecasting
• A/B Testing & Hypothesis Testing
ETL & Automation:
• Web Scraping – BeautifulSoup, Scrapy
• APIs – Fetch and process real-world data
• Build ETL Pipelines
Tools & Deployment:
• Jupyter Notebook / Colab
• Git & GitHub
• Cloud Platforms – AWS, GCP, Azure
• Google BigQuery, Snowflake
Hope it helps :)
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Quick recap of essential SQL basics 😄👇
SQL is a domain-specific language used for managing and querying relational databases. It's crucial for interacting with databases, retrieving, storing, updating, and deleting data. Here are some fundamental SQL concepts:
1. Database
- A database is a structured collection of data. It's organized into tables, and SQL is used to manage these tables.
2. Table
- Tables are the core of a database. They consist of rows and columns, and each row represents a record, while each column represents a data attribute.
3. Query
- A query is a request for data from a database. SQL queries are used to retrieve information from tables. The SELECT statement is commonly used for this purpose.
4. Data Types
- SQL supports various data types (e.g., INTEGER, TEXT, DATE) to specify the kind of data that can be stored in a column.
5. Primary Key
- A primary key is a unique identifier for each row in a table. It ensures that each row is distinct and can be used to establish relationships between tables.
6. Foreign Key
- A foreign key is a column in one table that links to the primary key in another table. It creates relationships between tables in a database.
7. CRUD Operations
- SQL provides four primary operations for data manipulation:
- Create (INSERT) - Add new records to a table.
- Read (SELECT) - Retrieve data from one or more tables.
- Update (UPDATE) - Modify existing data.
- Delete (DELETE) - Remove records from a table.
8. WHERE Clause
- The WHERE clause is used in SELECT, UPDATE, and DELETE statements to filter and conditionally manipulate data.
9. JOIN
- JOIN operations are used to combine data from two or more tables based on a related column. Common types include INNER JOIN, LEFT JOIN, and RIGHT JOIN.
10. Index
- An index is a database structure that improves the speed of data retrieval operations. It's created on one or more columns in a table.
11. Aggregate Functions
- SQL provides functions like SUM, AVG, COUNT, MAX, and MIN for performing calculations on groups of data.
12. Transactions
- Transactions are sequences of one or more SQL statements treated as a single unit. They ensure data consistency by either applying all changes or none.
13. Normalization
- Normalization is the process of organizing data in a database to minimize data redundancy and improve data integrity.
14. Constraints
- Constraints (e.g., NOT NULL, UNIQUE, CHECK) are rules that define what data is allowed in a table, ensuring data quality and consistency.
Here is an amazing resources to learn & practice SQL: https://bit.ly/3FxxKPz
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
SQL is a domain-specific language used for managing and querying relational databases. It's crucial for interacting with databases, retrieving, storing, updating, and deleting data. Here are some fundamental SQL concepts:
1. Database
- A database is a structured collection of data. It's organized into tables, and SQL is used to manage these tables.
2. Table
- Tables are the core of a database. They consist of rows and columns, and each row represents a record, while each column represents a data attribute.
3. Query
- A query is a request for data from a database. SQL queries are used to retrieve information from tables. The SELECT statement is commonly used for this purpose.
4. Data Types
- SQL supports various data types (e.g., INTEGER, TEXT, DATE) to specify the kind of data that can be stored in a column.
5. Primary Key
- A primary key is a unique identifier for each row in a table. It ensures that each row is distinct and can be used to establish relationships between tables.
6. Foreign Key
- A foreign key is a column in one table that links to the primary key in another table. It creates relationships between tables in a database.
7. CRUD Operations
- SQL provides four primary operations for data manipulation:
- Create (INSERT) - Add new records to a table.
- Read (SELECT) - Retrieve data from one or more tables.
- Update (UPDATE) - Modify existing data.
- Delete (DELETE) - Remove records from a table.
8. WHERE Clause
- The WHERE clause is used in SELECT, UPDATE, and DELETE statements to filter and conditionally manipulate data.
9. JOIN
- JOIN operations are used to combine data from two or more tables based on a related column. Common types include INNER JOIN, LEFT JOIN, and RIGHT JOIN.
10. Index
- An index is a database structure that improves the speed of data retrieval operations. It's created on one or more columns in a table.
11. Aggregate Functions
- SQL provides functions like SUM, AVG, COUNT, MAX, and MIN for performing calculations on groups of data.
12. Transactions
- Transactions are sequences of one or more SQL statements treated as a single unit. They ensure data consistency by either applying all changes or none.
13. Normalization
- Normalization is the process of organizing data in a database to minimize data redundancy and improve data integrity.
14. Constraints
- Constraints (e.g., NOT NULL, UNIQUE, CHECK) are rules that define what data is allowed in a table, ensuring data quality and consistency.
Here is an amazing resources to learn & practice SQL: https://bit.ly/3FxxKPz
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
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