https://github.com/manasjadhav0086/data-scraping-using-beautiful-soup
This project demonstrates how to scrape movie data from IMDb using Python. The notebook contains code to extract specific information about movies, such as their title, genre, release year, and more, for data analysis or visualization.
https://github.com/manasjadhav0086/data-scraping-using-beautiful-soup
beautifulsoup pandas reques
Last synced: 20 days ago
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This project demonstrates how to scrape movie data from IMDb using Python. The notebook contains code to extract specific information about movies, such as their title, genre, release year, and more, for data analysis or visualization.
- Host: GitHub
- URL: https://github.com/manasjadhav0086/data-scraping-using-beautiful-soup
- Owner: manasjadhav0086
- Created: 2024-12-06T18:30:45.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-12-06T18:37:28.000Z (5 months ago)
- Last Synced: 2025-02-13T03:30:02.472Z (2 months ago)
- Topics: beautifulsoup, pandas, reques
- Language: Jupyter Notebook
- Homepage:
- Size: 9.77 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Data Scraping on IMDb
This project demonstrates how to scrape movie data from IMDb using Python. The notebook contains code to extract specific information about movies, such as their title, genre, release year, and more, for data analysis or visualization.
---
## Introduction
IMDb is one of the most popular platforms for movie information, hosting details about films, television programs, cast, production crew, and much more. This project focuses on scraping and analyzing IMDb data programmatically.
---
## Features
- Extracts information about movies from IMDb.
- Handles data cleaning and storage for further analysis.
- Supports exporting scraped data to csv format.
- Modular code for flexible expansion or integration into larger pipelines.
---
## Requirements
To run this project, you need:
- Python 3.7 or later
- Jupyter Notebook or any Python IDE
- Internet connection (for accessing IMDb)
### Python Libraries
The following libraries are required:
- `requests` (for making HTTP requests)
- `BeautifulSoup` (for parsing HTML content)
- `pandas` (for data manipulation and storage)
---
## Usage
1. Open the notebook in Jupyter Notebook or Jupyter Lab.
2. Run each cell sequentially to execute the scraping workflow.
3. Modify target URLs or scraping parameters to suit your needs.
4. Export the scraped data for analysis or visualization.
---
## Output
The notebook generates cleaned and structured datasets, typically in CSV or JSON format, containing relevant movie details. These outputs can be used for analysis, visualization, or machine learning tasks.
---
## Acknowledgments
- **IMDb** for providing a comprehensive database of movie information.
- **BeautifulSoup** for making web scraping easy and intuitive.