Excel Data Analysis Projects

This repository contains multiple Excel-based data analysis projects, each focusing on different domains and data analysis techniques.

Project Structure

1. US Presidents Data Cleaning Project

Location: US_Presidents_Data_Cleaning/

This project demonstrates data cleaning techniques using US Presidents historical data.

Contents:

• US_Presidents_Data_Cleaning_Tutorial.xlsx: Excel workbook containing:
  • Raw data sheet ("need to clean")
  • Cleaned data sheet ("us Preident cleaned")
  • Data about US Presidents including:
    • President names
    • Prior experience
    • Political party
    • Vice presidents
    • Salary information
    • Date information

Data Cleaning Operations:

• Party name standardization
• Date formatting
• Data type conversions
• Missing value handling
• Duplicate detection

2. Bike Customer Demographics Analysis

Location: Bike_Customer_Demographics_Analysis/

A comprehensive analysis of customer demographics and bike purchase patterns.

Contents:

• Customer_Demographics_Bike_Purchase_Analysis.xlsx: Main analysis workbook containing:
  • Customer demographics data
  • Purchase decision analysis
  • Key metrics and insights

Data Analysis Features:

• Customer segmentation
• Purchase pattern analysis
• Demographic correlations
• Sales performance metrics

3. Healthcare Revenue Analysis

Location: Healthcare_Revenue_Analysis/

Analysis of healthcare revenue cycle and operational metrics.

Contents:

• Healthcare_Revenue_Analysis.xlsx: Processed and analyzed healthcare data
• Healthcare_Revenue_Raw_Data.xlsx: Source data for analysis
• Operation Analyst Case Study (2).pdf: Supporting documentation
• README.md: Project-specific documentation

Analysis Tools

This repository includes Python scripts for data analysis:

• analyze_data_cleaning.py: Script for analyzing data cleaning operations
• analyze_excel_story.py: Script for comprehensive Excel file analysis

Setup and Usage

1. Ensure you have Python installed with the following packages:

   • pandas
   • numpy
   • openpyxl

2. To analyze any Excel file, use the provided Python scripts:

   python analyze_data_cleaning.py
   python analyze_excel_story.py

Project Organization

Each project folder contains:

• Excel workbooks with raw and processed data
• Analysis results and visualizations
• Supporting documentation
• Data cleaning and transformation steps

Notes

• All Excel files contain detailed formulas and data transformations
• Data cleaning steps are documented within the workbooks
• Analysis methodologies are explained in the respective README files # Excel-Projects