Web Scraping + Data Analysis + Visualization (BeautifulSoup + Pandas + Matplotlib) for Beginners

Описание: Welcome to this step-by-step Python project tutorial! 🚀
In this video, we’ll go from Web Scraping → Data Analysis → Data Visualization — all in one session!
You’ll learn to scrape HTML data using BeautifulSoup (bs4), analyze it with Pandas, and visualize insights using Matplotlib.
Perfect for beginners looking to build a small but complete Data Science mini project.

🧩 Topics Covered & Timestamps

0:00 – Introduction & What We’ll Learn
0:06 – Overview: Web Scraping + Pandas + Matplotlib
0:17 – Understanding the HTML file structure
0:28 – Identifying HTML tags and attributes to scrape (title, instructor, rating, etc.)
0:47 – Installing required libraries (beautifulsoup4, pandas, matplotlib)
1:04 – Importing libraries and setting up environment
1:48 – Opening and reading the HTML file safely with encoding
3:12 – Printing and previewing HTML content
3:39 – Parsing HTML with BeautifulSoup
4:21 – Creating a BeautifulSoup object using html.parser
4:28 – Finding all course cards with .find_all()
5:12 – Extracting multiple course blocks from HTML
6:03 – Looping through all cards and preparing to extract details
6:15 – Extracting course title using .find() and .text.strip()
7:39 – Extracting instructor name using nested .find() and .span
9:59 – Extracting course rating (float conversion)
11:42 – Extracting number of students (integer conversion + text cleaning)
13:56 – Extracting price and cleaning ₹ symbol
14:48 – Printing all extracted values (title, instructor, rating, students, price)
15:02 – Appending all rows into a list of lists for DataFrame
15:40 – Creating Pandas DataFrame with proper column names
16:42 – Viewing the final structured table
17:00 – Getting DataFrame info using .info()
17:50 – Summarizing dataset using .describe()
18:25 – Sorting & finding Top 3 Courses by Rating
20:00 – Finding Top 3 Courses by Students Enrolled
20:48 – Finding Cheapest & Most Expensive Courses (idxmin / idxmax)
22:56 – Creating a derived column: Estimated Revenue = price × students
23:59 – Finding Highest Revenue Course
24:28 – Starting Data Visualization with Matplotlib
24:39 – Line Chart: Course vs Rating
26:33 – Rotating X-axis labels for better readability
27:53 – Adding markers and adjusting line width
28:38 – Bar Chart: Students Enrolled per Course
30:34 – Customizing Bar Colors, Edges & Gridlines
31:28 – Pie Chart: Price Share per Course
33:48 – Adding start angle & percentage display
34:07 – Final Recap and Project Summary
34:27 – Outro: What we learned + next steps

🧠 What You’ll Learn
Basics of Web Scraping using BeautifulSoup
Cleaning & organizing data with Pandas
Performing Data Analysis with .info(), .describe(), .sort_values()
Creating Visualizations (Line, Bar, Pie charts) with Matplotlib
Building a complete Python Data Project from scratch

🧰 Libraries Used
beautifulsoup4
pandas
matplotlib

💡 Project Idea
Mini Project: Course Analytics Dashboard
Scrape course data from an HTML page
Analyze top-rated and most enrolled courses
Visualize insights to make data-driven conclusions

🔗 Learn More : https://chatgpt.com/share/6910f14e-c1...

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