Tech Layoffs: Exploring the Trends and Industry Shifts Coded by: Jason Phillip [email protected]

This repository contains the code and data for my data visualization project, which examines tech layoffs from 2020 to January 2023. As my first project using Python, the primary focus is on creating meaningful visualizations to analyze trends in tech layoffs across various industries.

Overview The project aims to understand the reasons behind the tech layoffs during the pandemic and how different industries within the tech world have been impacted. By analyzing data from layoffs.fyi and creating visualizations using Python, we can gain insights into the patterns and shifts in the tech landscape.

Key Findings All industries reliant on technology seem to be affected by these layoffs. There are noticeable differences in the distribution of layoffs across industries between 2020 and 2022. As companies mature, they tend to let go of a smaller proportion of their workforce. Over time, companies have been laying off a smaller proportion of their workforce. Data The data used in this project is sourced from layoffs.fyi, which is updated daily. As of January 2023, the dataset contains 1,859 observations, with each observation representing a company's layoff announcement.