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Worldwide Tech Employment Trends
Data Science and Analytics
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About
This dataset provides a detailed account of reported worldwide layoffs in tech companies from 2020 to mid-2024. It offers valuable insights into the tech industry's employment trends, economic shifts, and geographical impact of layoffs. The data, primarily sourced via web scraping, includes additional enriched columns such as company size before and after layoffs, GPS coordinates for headquarters, country, and continent information. It is ideal for exploratory data analysis, data visualization, and for those learning and practising data analysis in R.
Columns
- #: A unique identification number for each layoff event.
- Company: The name of the tech company that reported layoffs.
- Location_HQ: The city and state/region of the company's headquarters.
- Country: The country where the company's headquarters is located.
- Continent: The continent where the company's headquarters is located.
- Laid_Off: The specific number of individuals who were laid off in a given event.
- Date_layoffs: The exact date when the layoffs were announced or occurred.
- Percentage: The percentage of layoffs relative to the total company size before the event.
- Company_Size_before_Layoffs: The estimated total number of employees at the company prior to the layoffs.
- Company_Size_after_layoffs: The estimated total number of employees remaining at the company after the layoffs.
- Industry: The specific industry sector within tech that the company operates in.
- Stage: The stage of the company, such as private or public.
- Money_Raised_in_$_mil: The total amount of money raised by the company in millions of US dollars.
- Year: The year in which the layoffs occurred.
- lat: The latitude coordinate of the company's headquarters.
- lng: The longitude coordinate of the company's headquarters.
Distribution
The dataset is available in both CSV and XLSX (Excel) formats. Key files include
tech_layoffs_Q2_2024.csv, which covers all reported layoffs from 2020 up to June 30th 2024, and tech_layoffs_location.csv, which details headquarters locations with GPS data. Other available files include tech_layoffs.xlsx, tech_layoffs_til_Q1_2024.csv, and tech_layoffs_til_Q4_2024.csv. The tech_layoffs.xlsx file is approximately 186.51 kB, while a larger version is about 921.34 kB. One of the primary tables, "Sheet1", contains 1672 rows and 16 columns. The dataset is expected to be updated quarterly to reflect new information.Usage
This dataset is well-suited for a variety of applications, including:
- Exploratory Data Analysis (EDA) to uncover trends and patterns in tech layoffs.
- Data Visualization to graphically represent layoff statistics, geographical distributions, and industry impacts.
- Learning and Practising in R for aspiring data scientists and analysts.
- Market Research into the stability and growth of different tech sectors.
- Economic Impact Studies on the tech industry.
Coverage
The dataset covers worldwide layoffs in technology companies. Geographically, it includes specific country and continent information for company headquarters, along with precise latitude and longitude coordinates. The time range spans from 2020 through to June 30th 2024, with data collected on several dates including December 25th 2023, January 14th 2024, March 31st 2024, and July 5th 2024. It focuses on various company stages (e.g., private, public) and specific industries within the tech sector.
License
CC BY-NC-SA 4.0
Who Can Use It
This dataset is particularly suitable for:
- Beginner data analysts looking for a real-world dataset for practice.
- Business intelligence professionals tracking industry trends.
- Researchers and academics studying labor markets and the tech economy.
- Students learning data analysis, especially with R.
- Anyone interested in the dynamics of the tech industry and employment changes.
Dataset Name Suggestions
- Global Tech Layoffs 2020-2024
- Worldwide Tech Employment Trends
- Tech Industry Layoffs Dashboard
- Layoffs.fyi Dataset (2020-2024)
- Quarterly Tech Layoffs Report
Attributes
Original Data Source: Worldwide Tech Employment Trends
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