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📊 Numerical Computing Toolkit using NumPy

A modular Python-based command-line application that performs matrix operations and statistical analysis using NumPy.

This project demonstrates strong foundational skills in numerical computing, linear algebra, statistics, file handling, and object-oriented programming — essential for Data Science and Machine Learning.

🚀 Features

🔹 Matrix Operations

  • Matrix Addition
  • Matrix Subtraction
  • Matrix Multiplication
  • Transpose
  • Determinant Calculation
  • Inverse of Matrix
  • Input Validation & Error Handling

🔹 Statistical Analysis

  • Mean
  • Median
  • Variance
  • Standard Deviation
  • Minimum & Maximum
  • Correlation between datasets
  • CSV File Input Support
  • Manual Data Entry Option

🛠 Technologies Used

  • Python 3
  • NumPy
  • CSV Module
  • Object-Oriented Programming (OOP)

📂 Project Structure

Numerical-Computing-Toolkit/
│
├── main.py
├── matrix_operations.py
├── statistics_operations.py
├── sample_data.csv
└── README.md

⚙️ Installation

  1. Clone the repository:
git clone https://github.com/PankajHarabhare09/Numerical-Computing-Toolkit-Using-NumPy.git
  1. Navigate to project directory:
cd NumericalComputingToolkit

▶️ Running the Application

python main.py

Follow the menu options in the terminal.

📊 Sample CSV Format

Name,Math,Science,English
Pankaj,85,78,90
Rahul,70,88,76
Amit,92,81,85
Sneha,60,75,80

🎯 Learning Outcomes

  • Applied NumPy for efficient numerical computations
  • Implemented matrix algebra operations
  • Performed statistical analysis on structured datasets
  • Practiced modular and scalable Python architecture
  • Handled file input and real-world debugging scenarios

🔮 Future Improvements

  • Add Data Visualization (Matplotlib)
  • Convert to Pandas-based analytics
  • Build Streamlit Web App
  • Add logging functionality
  • Deploy as a hosted application