Data-Science-Learning-Journey

📚 My Data Science Learning Journey

Welcome to my structured learning repository. This is where I document my daily practice and progress in Data Science, focusing on Pandas, NumPy, and Data Visualization.

I follow a strict learning framework for every topic:
Objective → Concept → Code → Output → My Observation → What I Learned

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🐍 1. Pandas Library

Module	Topic	Notebook Link	Key Learning
Day 1	Basics & Exploration	https://github.com/Aryan1727/Data-Science-Learning-Journey/tree/main/Data-Science-learning-Journey/01_Pandas/Day1_Learnings	head(), tail(), shape, info(), describe(), filtering, sorting
Day 2	Data Cleaning (Missing Values)	Coming Soon	Handling NaN, filling/dropping null values
Day 3	Groupby & Aggregations	Coming Soon	groupby(), mean(), count()

🔢 2. NumPy Library

Module	Topic	Notebook Link	Key Learning
Day 1	Arrays & Basic Operations	Coming Soon	Creating arrays, slicing, broadcasting

📊 3. Data Visualization (Matplotlib / Seaborn)

Module	Topic	Notebook Link	Key Learning
Day 1	Matplotlib Basics	Coming Soon	Line plots, bar charts, customization

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🚀 How to View the Notebooks

1. Browse the folders based on the topic.
2. Open the .ipynb files directly on GitHub (GitHub automatically renders the outputs).
3. Read my observations inside the notebook to understand my thought process.

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📬 Connect with Me

• Name: Kunwar Aryan
• LinkedIn: https://www.linkedin.com/in/kunwar-aryan-630b26358/
• GitHub: https://github.com/Aryan1727