Data-Cleaning-in-SQL

🏘 Nashville Housing Data Cleaning using MySQl Workbench

Task

To ensure the data is clean and ready for analysis

Data Cleaning Process

• Step 1

The first process involved the changing of the salesdate column into desired data type

• Step 2

Replacing the null values of Property Address either using Case statement or Coalesce Update the table

• Step 3

Breaking Property Address into individual columns address,city,state This was done using Substring,locate,length and substring index

• Step 4

Changing Y and N to YES and NO using Case Statement Using case Statement to equate Y to YES and N to NO

• Step 5

Identifying and deleting null values Using window function to identifying null values i.e the values indicating a number higher than 1 are null

• Step 6

Delete the null values from the table Removing Redutant Columns Using Delete syntax to remove Salesdate,Taxdistrict,PropertyAddress and OwnerAdsress

SQL Fundamentals Used

Data Defination Language

The Alter and Drop commands were used in defining diffrent columns in the dataset

Data Manipulation Language

Insert,Update,delete commands manipulated diffrent columns in the dataset,

Data Query Language

Select

Case Statements, Coalesce

• replacing the null values in property Address column

Locate and Substring

• Breaking out Property Address into individual columns

Substring_index

• Identifying the delimeter in Owner Address column and breaking it into individual columns

Type of join

• The table was joined with itself while performing data manipulation