DATA PRECISION ENGINE

Welcome! This repository showcases several projects involving data scraping, cleaning, and advanced SQL querying. Here, you'll find detailed analyses, complex queries, and insightful results that demonstrate the power of SQL in handling real-world data.

Table of Contents

Introduction

Projects Overview

• Data Science Job Market Analysis
• Google Play Store Analysis

Upcoming Projects

Installation

Contributing

License

Contact

Introduction

This repository contains a series of projects focused on different aspects of SQL. Each project includes data scraping, data cleaning, and sophisticated SQL queries to derive meaningful insights.

Projects Overview

1. Data Science Job Market Analysis

Description

In this project, data on the data science job market was scraped from various job boards. The dataset was cleaned and processed, followed by the execution of multiple SQL queries to uncover trends and insights in the job market.

Data Collection

Source: Various job boards Tools Used: Python (BeautifulSoup, Requests), Pandas

• Data Cleaning
• Handling missing values
• Standardizing data formats
• Removing duplicates

SQL Queries

Concepts Used:

• JOINS
• CTEs
• Sub-queries
• Window functions

Example Queries:

SELECT jobs.title, companies.name, salaries.amount
FROM jobs
JOIN companies ON jobs.company_id = companies.id
JOIN salaries ON jobs.salary_id = salaries.id
WHERE salaries.amount > 100000;

Insights

• Key job market trends
• Trends in salaries

2. Google Play Store Analysis

Description

This project involved scraping data from the Google Play Store, cleaning the dataset, and performing complex SQL queries to analyze various aspects of the data.

Data Collection

Tools Used: Python (BeautifulSoup, Requests), Pandas

Data Cleaning , Handling missing values , Standardizing data formats , Removing duplicates

SQL Queries

Concepts Used:

• JOINS
• CTEs
• Sub-queries
• Window functions

Example Queries:

SELECT app_name, AVG(rating) as average_rating
FROM reviews
GROUP BY app_name
HAVING COUNT(*) > 1000
ORDER BY average_rating DESC;

Insights

• App rating distributions
• Popular app categories
• Trends in user reviews

Upcoming Projects

Stay tuned for more exciting projects involving diverse datasets and advanced SQL queries!

Installation

To get started with this repository, clone it to your local machine and set up the necessary dependencies.

git clone https://github.com/yourusername/DataPrecisionEnginey.git
cd DataPrecisionEngine

Contributing

We welcome contributions! Please read our Contributing Guidelines for more details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any questions or feedback, please feel free to reach out:

Email: paramveers9451@gmail.com