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Welcome to our data exploration and cleaning repository, where we delve into the intricacies of COVID-19 dataset and Nashville housing data. This project aims to showcase different techniques to explore and clean the data using SQL.

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Data Exploration & Cleaning Project πŸš€

Welcome to this exciting data exploration and cleaning project, guided by none other than Alext the Analyst! πŸ“Šβœ¨

Overview

This repository is dedicated to the dynamic journey of understanding and refining datasets using SQL for comprehensive exploration and cleaning. The primary focus lies on two key domains: COVID-19 Data and Nashville Housing Data.

Guided by Alext the Analyst πŸ“ˆ

Alext, your experienced guide in this data adventure, brings a wealth of knowledge in data analysis and exploration. Together, we'll leverage SQL to unravel insights and ensure our datasets are pristine for further analysis.

Purpose of the Project 🎯

1. COVID-19 Data Exploration 🌐

  • SQL Exploration Techniques:
    • Utilize SQL queries to navigate through the COVID-19 dataset.
    • Uncover trends, patterns, and correlations within the data.
    • Apply aggregate functions to extract summary statistics.

2. Nashville Housing Data Cleaning 🧹

  • SQL Cleaning Functions and Techniques:
    • Address non-uniform data using CASE statements.
    • Standardize data formats with the CONVERTfunction.
    • Employ filtering conditions to remove outliers.
    • Populate data using self join.
    • Break out columns using SUBSTRING and PASENAME functions.
    • Remove duplicates and drop unused columns.
    • Implement the ROW_NUMBER() function for data ranking.

Collaboration and Feedback 🀝

This project thrives on collaboration! Whether you're a seasoned analyst or a curious learner, your input is valued. Share your thoughts, suggest improvements, and let's innovate together! 🌟

Happy coding and exploring! πŸš€βœ¨

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Welcome to our data exploration and cleaning repository, where we delve into the intricacies of COVID-19 dataset and Nashville housing data. This project aims to showcase different techniques to explore and clean the data using SQL.

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