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NashvilleProject_README.md

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Nashville Housing Data Cleaning and Transformation

  1. Welcome to the Nashville Housing Data Cleaning and Transformation project! 🏠
  2. This project focuses on preparing and optimizing the "NashvilleHousing" dataset within the "PortfolioProject" database for analysis and reporting purposes.
  3. The dataset contains valuable information about property sales in Nashville.

Project Objectives

The main objectives of this project are:

  • Standardize date formats.
  • Populate missing property addresses.
  • Split address fields into individual components (address, city, state).
  • Split owner address fields into individual components (address, city, state).
  • Update "SoldAsVacant" field values to standardized formats.
  • Remove duplicate records.
  • Delete unused columns to optimize the dataset.

Project Tasks Standardize Date Format:

  • Convert the "SaleDate" column to a standardized date format.

    Populate Property Address Data:

  • Identify and populate missing property addresses based on available data.

Split Address Fields:

  • Split the "PropertyAddress" field into individual components such as address, city, and state.

    Split Owner Address Fields:

  • Split the "OwnerAddress" field into individual components such as address, city, and state.

    Update "SoldAsVacant" Field:

  • Standardize "SoldAsVacant" field values to "Yes" or "No".

    Remove Duplicates:

  • Identify and remove duplicate records based on specific criteria.

    Delete Unused Columns:

  • Remove unnecessary columns such as "OwnerAddress", "TaxDistrict", "PropertyAddress", and "SaleDate" to optimize the dataset.G

Resources Required

  1. SQL Server or compatible database management system.
  2. Access to the "PortfolioProject" database.
  3. SQL script execution environment.

Risks and Mitigation

  • Data Loss: Regular backups has been taken before performing any modifications to mitigate the risk of data loss.

  • Data Integrity: Thorough testing will be conducted after each transformation step to ensure data integrity is maintained.

    Deliverables

  • Cleaned and transformed dataset ready for analysis.

  • Documentation outlining data cleaning and transformation processes.

    Success Criteria

  • Dataset is cleansed and standardized.

  • No critical data loss or corruption occurs during the cleaning process.

  • Transformation processes are documented for future reference.

    Note:

  1. This project plan outlines the steps, objectives, and resources required to clean and transform the Nashville housing dataset effectively.
  2. Further Adjustments can be made based on specific project requirements and constraints. Thank you for contributing to this project! 🚀