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Exploratory Data Analysis (Python)

πŸ“Š Project Overview

This project performs Exploratory Data Analysis (EDA) on a dataset using Python. The aim is to understand the structure, patterns, and relationships within the data.

πŸ”§ Tools & Libraries Used

  • Python
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn

πŸ“ Dataset

The dataset includes structured data used for analysis and visualization.

πŸ“Œ Key Features

  • Data cleaning and preprocessing
  • Handling missing values
  • Statistical summary of data
  • Data visualization using graphs and plots

πŸ“ˆ Insights

  • Distribution of variables
  • Relationships between features
  • Identification of trends and anomalies

πŸš€ How to Run

  1. Download the .ipynb file
  2. Open in Jupyter Notebook / VS Code
  3. Run all cells

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Exploratory Data Analysis (EDA) project using Python to uncover patterns, trends, and insights through data cleaning, statistical analysis, and visualization.

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