I enjoy working with data — cleaning it, analyzing it, and transforming it into meaningful stories through visualizations and dashboards. I also have experience building web-based projects and exploring cloud tools for scalable data workflows.
💡 Tip: SELECT * is convenient, but not always efficient.
- Built a Canvas using GitHub README and Actions
- A collaborative art experiment
- Analyzed study and habit patterns using Python (Pandas, NumPy)
- Derived insights on productivity trends during exam periods
- Used data cleaning, transformation, and visualization techniques
const pranav = {
languages: ["Python", "SQL", "R", "JavaScript", "Java", "HTML", "CSS"],
dataVisualization: ["Pandas", "NumPy", "Matplotlib", "Tableau", "Power BI"],
databases: ["MySQL", "PostgreSQL", "MongoDB"],
cloud: ["Google Cloud", "Firebase"],
currentlyWorkingOn: ["Data Analysis Projects", "Building Dashboards", "Improving SQL Query Performance"]
};
- Data Visualization using Power BI and Tableau
- Data Analysis with Python (Pandas, NumPy)
- Writing efficient SQL for real-world datasets
- Build Machine Learning models using scikit-learn
- Create advanced visualizations with ggplot2
- Work with cloud-based data pipelines (BigQuery, GCP)
- Apply R and SQL to larger, real-world datasets
Open to collaboration on data and web projects — reach out for discussions, ideas, or opportunities!
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