https://github.com/ariqf1/learn_data
Currently learning and building projects related to data pipelines, ETL processes, and data processing using Python. Passionate about scalable data solutions and modern data stack tools.
https://github.com/ariqf1/learn_data
data data-engineering mysql
Last synced: 2 months ago
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Currently learning and building projects related to data pipelines, ETL processes, and data processing using Python. Passionate about scalable data solutions and modern data stack tools.
- Host: GitHub
- URL: https://github.com/ariqf1/learn_data
- Owner: AriqF1
- Created: 2025-05-07T11:56:51.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-15T12:01:12.000Z (about 1 year ago)
- Last Synced: 2025-08-25T08:37:01.080Z (10 months ago)
- Topics: data, data-engineering, mysql
- Language: Jupyter Notebook
- Homepage:
- Size: 228 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 🏠 Mini Project Data Engineering: Analysis of Popular Topics in Kompas.com and Tribunnews.com
This project aims to analyze the most frequently reported news topics on May 6, 7, and 8, 2025 from two popular news portals in Indonesia: Kompas.com and Tribunnews.com. The goal is to see the tendency or focus of each media on certain issues.
 
## Installation
To install the necessary packages, run the following command:
```bash
pip install requests beautifulsoup4 pandas matplotlib
```
## 🛠 Tech
- Python - to perform web scraping from the website
- Requests & BeautifulSoup - library to scrapping data
- Pandas - data manipulation
- Matplotlib - data visualization
## Usage/Examples
Here's a basic example of how to use this project:
```python
import requests
from bs4 import BeautifulSoup
url = 'https://www.kompas.com/'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
# Example of extracting headlines
headlines = soup.find_all('h2')
for headline in headlines:
print(headline.text)
```
## Contributing
We welcome contributions! Please fork the repository and submit a pull request with your changes.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.