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SQL is a must-have skill for any aspiring data practitioner. Many modern companies store vast amounts of their data in various tables of relational databases. To extract the necessary data from a database for further manipulation and data analysis, you must have a good grasp of SQL. This repository serves as a showcase for my SQL projects

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analyst data-mining ddl-scripts dml-commands mysql-database sql sql-server-database sqlite3

sql-porfolio-projects-ddl-dml's Introduction

1.0 Covid 19 Data Exploration

Code: COVID Portfolio Project

Description: The dataset contains records of Covid-19 cases, deaths and vaccine records by country in 2020-2021. This project includes the following steps: data loading, data cleaning and preprocessing and EDA (exploratory data analysis).

Objective: Using SQL queries to provide insights into infection rates, death percentages, and vaccination progress at both global and regional levels. The results are stored in temporary tables and views for further analysis and visualization.

Skills: Joins, CTE's, Temp Tables, Windows Functions, Aggregate Functions, Creating Views, Converting Data Types

Technology: SQL Server

2.0 SQL Data Cleaning Queries: Nashville Housing.sql

Code: SQL Data Cleaning Queries: Nashville Housing.sql

Description: The dataset contains a list of houses that have been sold in Nashville between 2013 and 2019. This project includes the following steps: data loading, data cleaning and preprocessing.

Objective: To clean and enhance the NashvilleHousing data table by standardizing date formats, populating missing property addresses, breaking full addresses into individual components, converting specific values, removing duplicates, and deleting unused columns.

Skills: DML(Data Manipulation Language), DQL (Data Query Language), DDL (Data Definition Language).

Technology: SQL Server

3.0 Student Mental EDA SQL & Python

Code: Student Mental Analysis.ipynb

Description: Does going to university in a different country affect your mental health? Studying abroad can be both exciting and difficult. But what might be contributing to this? A Japanese international university surveyed its students in 2018 and published a study the following year that was approved by several ethical and regulatory boards.

The study found that international students have a higher risk of mental health difficulties than the general population, and that social connectedness (belonging to a social group) and acculturative stress (stress associated with joining a new culture) are predictive of depression.

Objective: To explore the students data using SQL and Python to find out if we can come to a similar conclusion for international students and see if the length of stay is a contributing factor.

Skills: DML(Data Manipulation Language), DQL (Data Query Language), DDL (Data Definition Language), Python (Pandas)

Technology: SQL Server , Notebook

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