Skip to main content
🌍 Public

Share visualization

Send this visualization to others.

Occupation, Salary, and Likelihood of Automation

Public visualization

Post on XLinkedIn

Viewing a saved revision (read-only)

9a97cd71b99f4a5eb4721443ace24829

Open

Occupation, Salary, and Likelihood of Automation

0 stars1🌍 Public
Ppszyarto@wpi.edu
Last edited Sep 4, 2025
Created on Sep 4, 2025

This bar chart visualizes U.S. occupational data, plotting the median annual wage for each occupation against its likelihood of automation across all 50 states. Users can switch between numeric columns (automation probability, employment, salary) using a dropdown menu, with an option to sort descending. Built with D3.js v7, the visualization uses `d3.scaleBand` and `d3.scaleLinear` to render SVG bars, dynamically detecting CSV columns and coercing string values to numbers for display.

AI-generated description

Dataset 2: Occupation, Salary, and Likelihood of Automation Source: Kaggle – Occupation, Salary, and Likelihood of Automation https://www.kaggle.com/datasets/andrewmvd/occupation-salary-and-likelihood-of-automation?utm_source=chatgpt.com Description This dataset links U.S. occupational data with automation probability scores, offering insights into how vulnerable different professions are to AI and automation. It also provides employment numbers and median salary estimates. This makes it valuable for exploring the tradeoff between wages, employment size, and automation risk. Attributes (VAD Framework) Attribute Type Notes Occupation Categorical Example: Cashier, Radiologist, Lawyer Automation Probability Quantitative Probability score (0–1) that the occupation can be automated Employment Quantitative Number of employed workers in that occupation Median Annual Wage (USD) Quantitative Median salary for the role Education Level Ordered Ordinal (e.g., High School < Bachelor’s < Master’s < Doctorate)