Data Analysis Projects

This repository contains three distinct data analysis projects. Each project explores different datasets using various data analysis techniques and tools.

Projects Overview

1. SQL Data Cleaning Project

Folder: SQL-Data-Cleaning-Project

This project contains SQL scripts for cleaning and standardizing data in the Nashville Housing dataset. The aim is to ensure data consistency, accuracy, and readiness for further analysis or reporting.

• Main file: SQLDataCleaning.sql
• Technologies used: SQL
• Key tasks: Standardizing date formats, handling null property addresses, breaking out addresses into individual columns, and more.

2. COVID-19 Data Exploration

Folder: Covid-Data-Exploration

This project involves exploring and analyzing COVID-19 data using SQL queries. The SQL script includes various queries to understand the impact of COVID-19 across different regions and demographics.

• Main file: Covid-Data-exploration.sql
• Technologies used: SQL
• Key tasks: Retrieving and ordering COVID-19 death records, analyzing total cases vs. total deaths, comparing total cases to population, summarizing COVID-19 impact by continent, and more.

3. Movie Correlation Project

Folder: Movie-Correlation-Project

This project explores correlations between various attributes of movies such as budget, gross earnings, and ratings using a dataset of movies. The analysis is performed using Python libraries such as pandas, numpy, seaborn, and matplotlib.

• Main file: Movie Correlation Project.ipynb
• Technologies used: Python, Jupyter Notebook
• Key tasks: Loading and inspecting the dataset, cleaning the data, performing exploratory data analysis (EDA), identifying correlations, and visualizing the results.