vrushali92 / SQL-Nashville-Data-Cleaning-

Cleaned the Nashville Housing Data

SQL-Nashville-Data-Cleaning

Cleaning the Nashville Housing Dataset using SQL.

I have cleaned this data using SQL statements. Here the data was retrieved, understood and then accordingly updated.

What was done?

• Converting String Date to Date datatype.
• Updating missing values in Address Column.
• Formating ParcelID, Acreage, LandValue
• Breaking out PropertyAddress, Owner Address into individual columns
• Change Y and N to Yes and No in 'SoldasVacant' field.
• Removing Duplicates and redudndant columns

Credits

This is a guided project from AlextheAnalyst: https://github.com/AlexTheAnalyst/PortfolioProjects/blob/main/Nashville%20Housing%20Data%20for%20Data%20Cleaning.xlsx

Files

• Dataset: Nashville_Housing_Data.xlsx in .csv
• Code: Nashville_Data_Cleaning.sql .sql

Setup

• Docker
• Azure Data Studio

Dataset

This dataset has 54403 records. It primarily describes the Nashville property's detail containing the Owner and its property details.

Description of the variables:

• UniqueID: Primary key
• ParcelID : varchar
• LandUse : varchar, Type of the property e.g Condo, Church, Apartment, Daycare
• PropertyAddress : varchar
• SaleDate: Date
• SalePrice: Integer
• LegalReference : varchar
• SoldAsVacant : Bool, Yes/ No
• OwnerName: varchar
• OwnerAddress : varchar
• Acreage : Float
• TaxDistrict : varchar
• LandValue : Integer
• BuildingValue : Integer
• TotalValue : Integer
• YearBuilt : Integer
• Bedrooms : Integer
• FullBath : Integer
• HalfBath : Integer