🐍 Data Analysis Using Python

This repository contains Python-based data analysis projects and practice exercises. It demonstrates skills in data cleaning, exploratory data analysis (EDA), visualization, and deriving insights using Python libraries(Pandas, Numpy, Matplotlib).

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📂 Repository Structure

• python_practice/ → Hands-on exercises for practicing data analysis workflows using Python.
• Capstone_project/ → A structured end-to-end project showcasing real-world data analysis.

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🛠️ Skills & Libraries Demonstrated

• Data Cleaning & Preparation: Handling missing values, duplicates, and outliers
• Exploratory Data Analysis (EDA): Descriptive statistics, correlation analysis, feature distributions
• Data Manipulation: Pandas & NumPy for data wrangling
• Capstone Project: End-to-end workflow with insights

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⚡ Example Workflows

1. Python Practice Examples

• Importing and cleaning raw datasets
• Performing descriptive statistics (mean, median, variance)
• Visualizing trends (bar charts, line plots, scatter plots)

2. Capstone Project

• Objective: Apply Python to analyze a real-world dataset and extract actionable insights.
• Steps:
  • Data Import & Cleaning
  • Exploratory Data Analysis
  • Visualizing key trends & correlations
  • Drawing business-level insights
• Tools: Pandas, NumPy, Matplotlib