Python Pandas overview

1. What is Pandas?

Pandas is a Python library used to work with data in table form.

In simple words:
👉 Pandas works like Excel in Python
👉 It helps you read, clean, and analyze data
👉 Very useful in Data Science and Data Analysis

2. Why Use Pandas?

We use Pandas because:
✔ Easy to understand
✔ Handles large data
✔ Works with CSV & Excel files
✔ Very powerful for analysis

3. Install Pandas

If Pandas is not installed, run:

4. Import Pandas

Example

👉 pd is a short name (standard practice).

5. What is a DataFrame?

A DataFrame is a table of data with:

• Rows

• Columns

Just like an Excel sheet.

6. Create a DataFrame (Basic)

Example

7. View Data from DataFrame

First Few Rows

Last Few Rows

8. Read Data from CSV File

Example

👉 Very common in real-world projects.

9. Basic Data Information

Example

10. Select Columns from DataFrame

Example

11. Select Rows from DataFrame

Example

12. Simple Data Analysis

Example

13. Filter Data (Very Useful)

Example

14. Add a New Column

Example

15. Real-World Example (Student Marks)

Example

16. Save Data to CSV File

Example

17. Common Beginner Mistakes

❌ Forgetting to install Pandas
❌ Using wrong column name
❌ Not checking data with head()
❌ Confusing rows and columns

18. Where Pandas is Used?

✔ Data Analysis
✔ Business Reports
✔ Data Cleaning
✔ Machine Learning
✔ CSV & Excel work

19. Pandas vs NumPy (Simple)

20. Summary (Python Pandas Overview)

✔ Pandas works with table data
✔ Uses DataFrame and Series
✔ Reads CSV & Excel easily
✔ Powerful and easy
✔ Very important for Data Science

📘 Perfect for Beginner Data Science eBook

This chapter is ideal for:

• Python learners

• Data Science beginners

• Students & professionals

• Career-focused readers

If you want next, I can write:

• Pandas Series Explained

• Pandas DataFrame Operations

• Pandas Filtering & Sorting

• Pandas Mini Projects

Just tell me 😊