Welcome to my Data Analytics Portfolio, which includes structured projects in both Data Science and Data Analysis, implemented in R and Python.
This repository is organized to reflect both the type of analytics and the programming language used, demonstrating a range of skills from exploratory data analysis to machine learning modeling.
Data Analytics/ ├── Data Science Project in Python/ ├── Data Science Project in R/ ├── Data Analysis Project in Python/ └── Data Analysis Project in R/
| Folder | Description |
|---|---|
Data Science Project in Python |
Predictive modeling, machine learning, or automation using Python libraries like scikit-learn, pandas, matplotlib, etc. |
Data Science Project in R |
Machine learning or statistical modeling using R packages such as caret, tidymodels, ggplot2. |
Data Analysis Project in Python |
Exploratory and descriptive analysis using Python for insights, visualizations and business reporting. |
Data Analysis Project in R |
Data wrangling, visualization and reporting using R’s powerful data analysis tools. |
- Languages: Python, R
- Libraries/Frameworks:
- Python: Pandas, NumPy, Matplotlib, Seaborn, scikit-learn
- R: tidyverse, ggplot2, dplyr, caret
- Others: Jupyter Notebook, RMarkdown, Git
This portfolio is intended to:
- Showcase a range of data analytics skills
- Provide examples of real-world project structure
- Demonstrate proficiency in both R and Python
- Serve as a learning and reference resource
Each subfolder is a standalone project. To explore:
- Navigate into any project folder
- Follow the individual
README.mdfor setup and details (if available) - Open notebooks or R scripts for code and results
For questions, feedback or collaboration:
- 📧 Email: gmail
- 🌐 LinkedIn: linkedin-profile
Note: This portfolio is a work in progress. More projects and documentation will be added regularly.