📊 Data Handling & Visualization Journey

Welcome to my repository where I document my weekly explorations in data analysis and visualization. Every week, I pick a different dataset, dive deep into data cleaning, transformation, and visual exploration, and share my work as a Google Colab notebook.

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🚀 Purpose

This project is my personal journey to:

• Strengthen my data handling skills
• Explore various datasets across domains
• Apply different visualization techniques
• Build a consistent habit of weekly data exploration

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📅 Project Structure

Each week’s work is stored in a separate folder:

📁 Week-1_Titanic Dataset/
    ├── Data Handling and Visualisation on the Titanic Dataset.ipynb  # Google Colab notebook
    ├── dataset.csv     

📁 Week-2_Iris Dataset/
    ├── DHV on the Iris Dataset.ipynb
    └── ...

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🔍 Topics Covered

Throughout this journey, I’ll be exploring:

• Data Cleaning: handling missing values, duplicates, and outliers
• Data Transformation: feature engineering, encoding, scaling
• Exploratory Data Analysis (EDA): statistical summaries & visual insights
• Visualization: histograms, scatter plots, heatmaps, interactive plots
• Tools & Libraries: pandas, numpy, matplotlib, seaborn, plotly

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🛠 Tech Stack

• Python 3.x
• Jupyter / Google Colab
• pandas, numpy, matplotlib, seaborn, plotly

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📈 Progress Tracker

Week	Dataset	Key Focus
1	Titanic	EDA & Basic Visualization
2	Iris Dataset	Cleaning & Feature Engineering
...	...	...

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🤝 Contributions

This is a personal learning project, but if you have interesting dataset suggestions or ideas for visualization challenges, feel free to open an issue or drop a comment.

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📬 Connect

• GitHub: [https://github.com/aditivermaa04]

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