🧮 NumPy Practice Projects

Welcome to a collection of hands-on NumPy practice projects designed to strengthen understanding of array operations, broadcasting, matrix math, and real-world data manipulation using Python and NumPy.

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📁 Projects List

1. 🧮 Matrix Calculator

Builds a matrix calculator capable of:

• Addition, subtraction, multiplication
• Transpose
• Inverse & determinant (for square matrices)

📂 matrix_calculator/
📄 Features: Input validation, interactive CLI, NumPy linear algebra functions

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2. 🎲 Dice Roll Simulation

Simulates 100,000 rolls of two dice:

• Visualize outcome frequency
• Calculate probability of each sum

📂 dice_roll_simulation/
📄 Focus: NumPy random generation, histograms, statistical insight.

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3. 🖼️ Image Processing with NumPy

Applies basic image processing using NumPy:

• Convert RGB to Grayscale
• Flip horizontally/vertically
• Rotate 90°
• Apply basic blur filter (box blur)

📂 image_processing_numpy/
📄 Features: Works with any .jpg image using Pillow and NumPy.

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4. 🌦️ Weather Data Analysis

Simulates and analyzes temperature data:

• Calculate average, max/min temperature
• Identify hottest/coldest days
• Optional: rolling averages and simple plotting

📂 weather_data_analysis/
📄 Great for applying aggregation, indexing, and vectorized stats.

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5. 📈 Stock Price Simulator

Generates stock price trends using:

• Geometric Brownian Motion
• Monte Carlo-style randomness

📂 stock_price_simulator/
📄 Focus: NumPy math, np.exp, np.cumsum, simulations

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6. 📊 Custom Statistics Calculator

Implements common statistics manually:

• Mean, median, mode
• Standard deviation, percentiles
• Z-score

📂 statistics_calculator/
📄 Helps you practice both built-in and manual NumPy stat functions.

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7. 🔢 Sudoku Validator

Checks if a completed Sudoku grid is valid:

• Row, column, and sub-grid checks
• Uses slicing, reshaping, and set comparisons

📂 sudoku_validator/
📄 Focus: Logical checks using NumPy indexing.

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8. 🎥 Movie Ratings Analyzer

Analyzes fake or real user-movie ratings:

• Calculate averages
• Find top-rated movies
• Build a simple recommendation logic

📂 movie_ratings_analyzer/
📄 Focus: 2D arrays, aggregation, logic with axis=0 and axis=1

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🛠 Requirements

Install dependencies with:

pip install numpy pillow

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👤 Author

Shadan Tech
Data Analyst 🔗 LinkedIn Profile
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