📊 Data Science Job Market Insights

Overview

Welcome to the Data Science Job Market Insights repository! 🎉 This project dives into the data science job market using data scraped from Indeed.com. We’ve cleaned, analyzed, and visualized the data to uncover insights about job trends, required skills, and salary distributions across the United States.

Project Components

1. Data Collection 🗃️

• Scraped Data Science job listings from Indeed.com.
• Collected details like job titles, required skills, salaries,education required and locations and more.

2. Data Cleaning 🧹

• Processed and cleaned raw data collected by scraping .
• Perfromed Data engineering by extracting and creating new formatted data columns .

3. Tableau Dashboards 📊

• Created interactive dashboards in Tableau to visualize insights:
  • Top skills required by top employers
  • Skill distribution across salary ranges
  • Salary distribution analysis
  • Education Level demand
  • Geographic distribution of on-site job requirements
  • Dashboard

Getting Started 🚀

Prerequisites

• Python
• Tableau (for visualization)
• Google Colab / Jupyter Notebook
• Visual Studio Code or any python compiler of choice
• Required Python libraries: selenium, pandas, numpy

Installation

1. Clone the repository:

   git clone https://github.com/Arian-Rahman/Data-Science-Job-Market-Insights.git

2. Navigate to the project directory:

   cd data-science-job-market-insights

3. Create virtual env (windows)

   python -m venv envDsInsights

4. Activate the new env

   .\envDsInsights\Scripts\activate
   

5. Install required Python libraries:

   pip install -r requirements.txt
   

Usage

1. Data Scraping:

   • Run scrap_v4.01.py to collect data from Indeed.com .

2. Data Cleaning:

   • Run Final_P01.03_data_cleaning.ipynb on Colab or Jupyter Notebook for data cleaning.

3. Data Analysis & Visualization:

   • Open Tableau and load Data Science Job Viz from Indeed.com.twbx to explore the dashboard.
   • Click on the data section and import the data from data folder