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SQL project analyzing company layoffs over the past 3–4 years. Includes data cleaning (handling duplicates, nulls, formatting, standardize data ) and exploratory data analysis (EDA) to identify layoff trends.

an experimental layoff tracking repo for the recent tech layoffs in the United States

Performed data visualization using Tableau to track and analyze tech layoffs trends. Obtained data from Kaggle, utilized various charts to communicate insights, user-friendly interface.

This project is about cleaning and preparing a global layoffs dataset for analysis, focusing on handling null values, correcting data types, and ensuring data integrity for more accurate insights.

The story of a layoffs playlist

This repository contains SQL files of the queries I have used to clean and explore a dataset which consists information on layoffs worldwide from 2021-2023

This Datasets is of World layoffs so i have done analysis with the help of MySql

UC Davis STA 220 Web Scraping Project

Python VAR implementation of "Macroeconomic Variables that directly affects the Layoffs in Tech Sector"

SQL-based data analysis project examining layoffs during 2022-2023, with insights into industry trends, company impacts, and workforce dynamics.

Recently, Meta lately let go 13% of its staff, or further than 11,000 people, due to the recent profitable recession. This dataset was created with the expedients that it'll help the Kaggle community examine the current technological earthquake and unearth perceptive facts.

This project cleans and analyzes a tech layoffs dataset using MySQL and Python (Pandas) to compare their efficiency in data processing. It provides business insights into workforce trends, industry stability, and economic impacts to support data-driven decision-making.

Visualizing the Impact of Layoffs

Performed EDA using SQL to track and analyze layoffs trends. Obtained data from Kaggle, utilized various processes to communicate various insights.

Unofficial project to automatically run BigLocalNews' WARN (layoff notice) scraper, commit what it finds