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.
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Updated
Aug 30, 2024
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.
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Python VAR implementation of "Macroeconomic Variables that directly affects the Layoffs in Tech Sector"
UC Davis STA 220 Web Scraping Project
Performed EDA using SQL to track and analyze layoffs trends. Obtained data from Kaggle, utilized various processes to communicate various insights.
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.
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.
an experimental layoff tracking repo for the recent tech layoffs in the United States
Unofficial project to automatically run BigLocalNews' WARN (layoff notice) scraper, commit what it finds
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