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).
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.
- 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
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