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This repository contains a comprehensive analysis of business employment data for different industries. The primary focus is top assess the revisions in filled job figures and earnings up to the year 2023.

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farhansadeed/Python-Business-Employment-Data-Analysis

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Business Employment Data Analysis (Up to 2023)

👨‍🎓Dashboard::atom:

Trend of Filled Jobs Across Quarters by Industry Fig 1: Trend of Filled Jobs Across Quarters by Industry

Percentage Difference in Filled Jobs and Earnings by Industry December 2022 Fig 2: Percentage Difference in Filled Jobs and Earnings by Industry December 2022

Heatmap of Percentage Difference in Filled Jobs Across Industries and Quarters Fig 3: Heatmap of Percentage Difference in Filled Jobs Across Industries and Quarters

Dataset Overview

The dataset provides a quarterly breakdown of:

  • Original and revised figures for filled jobs.
  • Original and revised figures for total earnings.
  • Percentage differences between original and revised figures.

Primary Observations

  1. Trends in filled jobs across different quarters for each industry.
  2. Percentage difference in filled jobs and earnings for each industry in December 2022.
  3. A heatmap visualizing the percentage difference in filled jobs across industries and quarters.

Tools Used

  • Python: For data analysis.
  • Pandas: For data manipulation and cleaning.
  • Matplotlib: For creating visualizations.
  • Seaborn: For enhanced data visualization capabilities.


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This repository contains a comprehensive analysis of business employment data for different industries. The primary focus is top assess the revisions in filled job figures and earnings up to the year 2023.

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