This project is an analysis aimed at providing an in-depth look into the massive layoffs that happened in the tech industry since mid-2022.
The dataset used in this project is "Technology Company Layoffs (2022-2023)" and it contains information on 450+ technology companies who have announced a layoff or is known to have laid off their employees between mid-2022 to 2023. The main objectives of this project are:
- Visualizing current layoffs trends based on months
- Identifying which locations are most impacted
- Whether IPO status affects severity of layoffs
The original data is stored under the 'data' folder, while the clean one is generated inside the 'notebook' folder.
The following is a description of the columns used in this dataset.
- total_layoffs - number of total layoffs so far
- impacted_workforce_percentage - % of impacted workforce (based on pre mid-2022 company size)
- reported_date - when first layoff or plan to layoff was announced
- industry - more information on segment in which the company operates
- headquarter_location - HQ of company
- sources - data sources/news outlets
- status - whether company is public or private (IPO status)
- additional_notes - More details on layoffs (or future layoffs) plan
To run the code for this project, follow these steps:
- Clone the repository to your local machine.
- Run the Jupyter notebook(s) in the repository to reproduce the analysis and generate the visualizations.
This project contains thorough exploratory data analysis for the provided data. The following are additional research questions that potential stakeholders may ask:
- Which companies have the highest total number of layoffs?
- What is the average impacted workforce percentage across all companies?
- Has the number of layoffs increased or decreased over time?
- Which industries have been affected the most by layoffs?
- Are there any geographic patterns in terms of where layoffs are happening (e.g. specific states or regions)?
- What are the sources of the data, and how reliable are they?
- How up-to-date is the data, and how frequently is it updated?
- Are there any notable differences in the reported data for publicly traded companies versus privately held companies?
- What is the status of the reported layoffs (e.g. ongoing, resolved, etc.)?
- Can you provide additional insights or analysis to help explain the reasons for the layoffs and their impact on the affected employees and communities