Hi all,

Here's the link for pandas day-4 video.


English :- https://youtu.be/UaoseR5HnUY?si=7jz5SRkaoNzrIb1U


Hindi:-
https://youtu.be/jQTKaqRjVos?si=9k9XGnv7nobEDQZT


I'm waiting for you all in the comment section.


✅Share it with your fellow learners.


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Data science interview questions 👇

𝗦𝗤𝗟
- How do you write a query to fetch the top 5 highest salaries in each department?
- What’s the difference between the HAVING and WHERE clauses in SQL?
- How do you handle NULL values in SQL, and how do they affect aggregate functions?

𝗣𝘆𝘁𝗵𝗼𝗻
- How do you handle large datasets in Python, and which libraries would you use for performance?
- What are context managers in Python, and how do they help with resource management?
- How do you manage and log errors in Python-based ETL pipelines?

𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴
- Explain the difference between bias and variance in a machine learning model. How do you balance them?
- What is cross-validation, and how does it improve the performance of machine learning models?
- How do you deal with class imbalance in classification tasks, and what techniques would you apply?

𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴
- What is the vanishing gradient problem in deep learning, and how can it be mitigated?
- Explain how a convolutional neural network (CNN) works and when you would use it.
- What is dropout in neural networks, and how does it help prevent overfitting?

𝗗𝗮𝘁𝗮 𝗪𝗿𝗮𝗻𝗴𝗹𝗶𝗻𝗴
- How would you handle outliers in a dataset, and when is it appropriate to remove or keep them?
- Explain how to merge two datasets in Python, and how would you handle duplicate or missing entries in the merged data?
- What is data normalization, and when should you apply it to your dataset?

𝗗𝗮𝘁𝗮 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 - 𝗧𝗮𝗯𝗹𝗲𝗮𝘂
- How do you create a dual-axis chart in Tableau, and when would you use it?
- How would you filter data in Tableau to create a dynamic dashboard that updates based on user input?
- What are calculated fields in Tableau, and how would you use them to create a custom metric?

#datascience #interview

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7 Best GitHub Repositories to Break into Data Analytics and Data Science

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Provides a default value for a column when no value is specified.
✔️ Helps in avoiding NULL values in columns where default values make sense.

✅ Example of DEFAULT Constraint

CREATE TABLE Orders (
    OrderID INT PRIMARY KEY,
    CustomerName VARCHAR(50),
    OrderDate DATE DEFAULT CURRENT_DATE
);

✔️ If OrderDate is not provided, it automatically gets the current date.

✅ Inserting Data (Valid Cases)

INSERT INTO Orders (OrderID, CustomerName) VALUES (1, 'Alice'); -- ✅ OrderDate is set to today's date
INSERT INTO Orders (OrderID, CustomerName, OrderDate) VALUES (2, 'Bob', '2025-01-01'); -- ✅ Valid, custom date given

---

🔹 Summary of SQL Constraints

| Constraint | Ensures | Can Be NULL? | Allows Multiple in a Table? |
|--------------|---------------------------------|--------------|--------------------------|
| PRIMARY KEY | Uniqueness & Non-null values | ❌ No | ❌ No (Only One) |
| FOREIGN KEY | Referential Integrity | ✅ Yes (If NULL allowed) | ✅ Yes |
| UNIQUE | Uniqueness (without Primary Key) | ✅ Yes | ✅ Yes |
| CHECK | Enforces condition on values | ✅ Yes | ✅ Yes |
| DEFAULT | Provides a default value | ✅ Yes | ✅ Yes |

---

🔹 Your Task for Today
✅ Create a Students & Courses database using all the constraints.
✅ Try inserting valid & invalid values to see how constraints work.
✅ Comment below if you have any questions! 💬

---

🔹 What’s Next?
Tomorrow, we will learn Creating and Managing Indexes! Stay tuned! 🚀

💡 Like ❤️ & Share if you're enjoying this SQL series! 😊

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- Learn new things
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