🧹 President Information – Data Cleaning (Excel Project)

This repository showcases a data cleaning project performed entirely in Microsoft Excel, using a dataset of U.S. Presidents. The work includes identifying and correcting inconsistencies, formatting data for readability, and preparing the dataset for future data analysis or visualization.

📊 Dataset Overview

The dataset contains historical information about U.S. Presidents, including:

• President Name
• Political Party
• Vice President
• Salary
• Date Created
• Date Updated
• (Originally included more columns like “prior role” and row indexes)

✅ Data Cleaning Process

All cleaning was done manually using Excel formulas, formatting tools, and filters. Below are the key changes made:

🔧 Removed Redundancies & Irrelevant Data

• Deleted the index column (Unnamed: 0) and unnecessary metadata.
• Removed the “prior” column due to inconsistent formatting and encoding errors.

👤 Standardized Names

• Fixed inconsistent casing (e.g., john adams, JAMES MONROE) by converting all names to title case.
• Trimmed extra spaces within names (e.g., George Clinton → George Clinton).

🏛️ Party Standardization

• Standardized inconsistent party names like:
  • Democratic- Republican → Democratic-Republican

💼 Cleaned Salary Data

• Verified numeric consistency and formatting for the salary column.

📅 Date Format Fixes

• Ensured all date_created and date_updated fields follow the standard ISO format: YYYY-MM-DD.

📁 Repository Contents

• President Information - Data Cleaning.xlsx: The Excel file containing:
  • US_Presidents Data – original raw dataset
  • US_Presidents Data Fixed – cleaned and formatted version

🛠️ Tools Used

• Microsoft Excel (no code required!)
  • Find & Replace
  • Text functions (e.g., PROPER(), TRIM())
  • Filter and Sort
  • Manual inspection and correction

🚀 Potential Next Steps

• Export cleaned dataset to CSV for public data analysis.
• Visualize trends in U.S. Presidential data (e.g., salaries, party changes).
• Augment dataset with additional fields like education, birthplace, or term years.

👥 Contributor

• Azim Nahin