goated69/mauritius-it-jobs
Mauritius IT Jobs Dataset This dataset contains IT job listings scraped from myjob.mu, the primary job board in Mauritius. This dataset is part of the MyJobViz project, which provides visualization and analysis tools for the Mauritius IT job market. Dataset Structure Each job listing contains the following fields: Field Type Description job_title string Title of the job position company string Name of the hiring company date_posted datetime When the… See the full description on the dataset page: https://huggingface.co/datasets/goated69/mauritius-it-jobs.
Mauritius IT Jobs Dataset
This dataset contains IT job listings scraped from myjob.mu, the primary job board in Mauritius.
This dataset is part of the MyJobViz project, which provides visualization and analysis tools for the Mauritius IT job market.
Dataset Description
- Source: myjob.mu
- Geographic Focus: Mauritius
- Job Category: Information Technology (IT) only
- Collection Period: 2022 - Present
- Last Backup: 2026-09-01_06-56-07
- Total Jobs: 9,869
Dataset Structure
Each job listing contains the following fields:
Example Entry
{
"job_title": "it helpdesk support - raw it services ltd",
"company": "TAYLOR SMITH GROUP",
"date_posted": 1676332800000,
"closing_date": 1678924800000,
"location": "Port Louis",
"employment_type": "Trainee",
"salary": "10,000 - 20,000",
"job_details": "Your role will consist of providing support to the technical team...",
"url": "http://myjob.mu/Jobs/IT-Helpdesk-Support-Raw-IT-141921.aspx",
"timestamp": 1676427651200
}Files
jobs.json: Complete job listings in JSON formatjobs.csv: Complete job listings in CSV format (easier to preview)metadata.json: Backup metadata and statistics
Usage
Load with HuggingFace Datasets
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("goated69/mauritius-it-jobs")
print(dataset)Load with Pandas
import pandas as pd
# From CSV
df = pd.read_csv("hf://datasets/goated69/mauritius-it-jobs/jobs.csv")
# From JSON
df = pd.read_json("hf://datasets/goated69/mauritius-it-jobs/jobs.json")
# Convert timestamps to datetime
df['date_posted'] = pd.to_datetime(df['date_posted'], unit='ms')
df['closing_date'] = pd.to_datetime(df['closing_date'], unit='ms')
df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')Potential Use Cases
- Job Market Analysis: Analyze trends in Mauritius IT job market
- Salary Research: Study compensation patterns for IT roles
- Skills Demand: Identify most in-demand technologies and skills
- Location Analysis: Understand geographic distribution of IT jobs
- Time Series Analysis: Track job posting trends over time
- NLP Tasks: Job description classification, entity extraction, skill identification
- Career Planning: Research companies, job titles, and requirements in Mauritius IT sector
Data Collection
Data is collected through automated web scraping of myjob.mu, focusing exclusively on IT-related job postings. The scraper runs periodically to capture new job listings.
Scraping Code: The code used to scrape and process this data is available at github.com/creme332/myjobviz
Limitations
- Only includes IT jobs (other sectors not included)
- Geographic scope limited to Mauritius
- Dependent on data availability from source website
- Some fields may contain inconsistent formatting (e.g., whitespace in location field)
- Salary information may be missing or in various formats
Statistics
The statistics.json file (if included) contains aggregated data on:
- Programming languages mentioned in job descriptions
- Technologies and frameworks (databases, cloud platforms, tools)
- Job title distributions
- Location distributions
- Salary ranges
- And more...
Citation
If you use this dataset in your research or analysis, please cite:
Mauritius IT Jobs Dataset, scraped from myjob.mu
Part of the MyJobViz project: https://github.com/creme332/myjobviz
Available at: https://huggingface.co/datasets/goated69/mauritius-it-jobsLicense
This dataset is provided under CC-BY-4.0 license. The data is scraped from publicly available job listings.
Backup History
This dataset is automatically updated with regular backups to preserve historical job market data.
Last Updated: 2026-09-01_06-56-07
