Dataframe in Python Pandas | Class 12 IP (ONE SHOT) | CBSE 2025-26 | Rohit Singh

Dive into the complete chapter “Data Handling using Pandas – I (DataFrame)”, designed especially for CBSE Class 12 Informatics Practices (IP) students (2025–26 syllabus).

In this session, you’ll create, modify, and analyse data using Pandas DataFrames — the most powerful data structure in Python, essential for data analysis and board exams.
Every concept is taught step-by-step with clarity, code, and board-oriented examples.

📘 What You’ll Learn
🔹 What is a DataFrame and why it’s important
🔹 Creating DataFrames from Dictionary, List, and Series
🔹 Accessing Data using loc[], iloc[], at, and iat
🔹 Boolean Indexing & Conditional Filtering
🔹 Adding, Deleting, and Renaming Rows & Columns
🔹 Sorting & Modifying Data in DataFrames
🔹 DataFrame Attributes & Methods (head(), tail(), etc.)
🔹 Importing & Exporting Data with CSV (read_csv(), to_csv())
🔹 Practice Questions + Exam-focused Concepts

💡 Who Should Watch
✔️ Class 12 IP & CS students (CBSE 2025–26)
✔️ BCA, MCA, B.Tech, M.Tech learners mastering Python for data handling
✔️ Students preparing for boards, practicals, or viva

👨‍🏫 Instructor
Rohit Singh
PGT Computer Science | 10+ Years of Teaching Experience
🖥️ Computer Science | 💡 Informatics Practices | 🤖 Artificial Intelligence

📘 Notes: https://drive.google.com/file/d/1lyTVLVtrmmIYQuUPls1gG7W9L62AFvKW/view?usp=sharing

💬 Join CBSE Class 11–12 WhatsApp Group: https://chat.whatsapp.com/LW4dBrAHIaGAXwK1ni2MPH

📍 Offline Classes: Sant Nagar & Hudson Lane
📞 Coaching Enquiries: 8800873871

⏱️ Timestamps – Jump to Any Topic
(Python Pandas DataFrame | Class 12 IP | CBSE Data Handling using Pandas)

Part A – Introduction to DataFrame
00:00 – Introduction
00:38 – What is a DataFrame?
02:09 – Creating an Empty DataFrame
03:13 – Creating a DataFrame using Dictionary
06:04 – Retrieving a Single Column
08:36 – Retrieving Multiple Columns
10:23 – Arithmetic & Relational Operations

Part B – Accessing Data in a DataFrame
19:38 – Accessing Single Values using at and iat
23:20 – Accessing Multiple Values using loc and iloc
32:40 – Boolean Indexing

Part C – Modifying DataFrame
33:35 – Adding & Modifying Rows
35:28 – Adding & Modifying Columns
37:24 – Using insert() Function
38:47 – Deleting Rows & Columns (drop(), pop(), del)
43:48 – Renaming Row and Column Labels
46:49 – Sorting Data in a DataFrame

Part D – Attributes & Methods
47:51 – DataFrame Attributes
52:02 – Methods: head(), tail(), count()

Part E – Working with CSV Files
53:33 – Importing CSV (read_csv())
57:40 – Exporting DataFrames (to_csv())

Outro
59:44 – Thank You & Subscribe Reminder

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