📊Data_mining_R_and_Python

Hey there! 👋 This is a personal learning project where I'm exploring data mining using both R and Python — mostly focused on scraping, retrieving, and preparing data that I plan to use later for training machine learning models (also part of my learning journey!).

I'm still in the beginner phase, so this repo is more of a hands-on playground for experimenting, making mistakes, and figuring things out as I go. If you're learning too, feel free to follow along!

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📚 Table of Contents

• 🧠 What This Repo Is About
• 📁 Folder & Script Info
• 🛠 Requirements
• 🚀 Getting Started
• 🌱 Learning Goals
• 💬 Notes
• ⭐️ Support the Journey
• 🔖 Hashtags

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🧠 What This Repo Is About

• Collecting data from various sources using R and Python
• Prepping and cleaning the data to make it usable
• Structuring the datasets for future ML experiments
• Keeping things as simple and understandable as possible

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📁 Folder & Script Info

You'll find two types of scripts here:

🔵 R Scripts

• Scrape or retrieve data using libraries like rvest or httr
• Convert and clean raw data
• Store it for later ML use

🟠 Python Scripts

• Scrape websites using requests, BeautifulSoup, or Selenium
• Convert scraped content to structured formats (CSV, JSON)
• Prep the data for ML tasks using libraries like pandas

The code might be a little messy or commented for my own understanding — it's all part of the learning process.

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🛠 Requirements

For R

• R (version 3.6 or higher recommended)
• RStudio (optional but helpful)
• These packages installed:

install.packages(c("rvest", "httr", "jsonlite", "dplyr"))

For Python

• Python 3.7+
• Recommended to use a virtual environment
• Required packages:

pip install requests beautifulsoup4 pandas selenium

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🚀 Getting Started

1. Clone the repo:

git clone https://github.com/amehnd/Data_mining_R_n_Python.git

2. Choose a script (.R or .py) and run it in your environment
3. Experiment, modify, break things, and learn from it
4. Document what you learn (like I do here)

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🌱 Learning Goals

• Get better at scraping and handling data using both R and Python
• Learn how to clean, transform, and prepare datasets for ML
• Build confidence in data engineering skills before diving deeper into ML

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💬 Notes

• This project is a learning log, not a polished product
• I'm learning as I go — so if you see something that can be improved, feel free to share!
• Suggestions, tips, or PRs are welcome (as long as they’re kind ✌️)

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⭐️ Support the Journey

If this repo helped you or you're also learning —
make sure to give it a star ⭐️ and follow along as I keep building and learning!

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🔖 Hashtags

#rstats #Python #WebScraping #DataMining #MachineLearning #LearningInPublic #DataScience