pszyarto@wpi.edu

Global AI Content Impact Dataset - Set8

This interactive scatterplot and trend explorer visualizes AI adoption and impact metrics across countries, industries, and years from a synthetic CSV dataset. Users filter by year and industry, with hover tooltips revealing details. The D3.js v7 visualization uses SVG rendering, featuring zooming/panning via `d3.zoom` and coordinated view switching between scatter and trend modes. State persists through URL hash parameters, and data loading handles both tab-separated and comma-separated CSV formats.

Global AI Content Impact Dataset - Set7

This interactive scatterplot explores a synthetic dataset of AI adoption across countries and industries, mapping variables like adoption rate, job loss, and revenue growth. Users can filter by year, highlight industries, and select between scatter and trend views. Built with D3 v7, the visualization uses SVG rendering, a view switcher tied to URL hash state, and dynamic data loading from a CSV file.

Global AI Content Impact Dataset - Set6

This scatter plot visualizes the Global AI Content Impact Dataset, mapping AI adoption rates against job loss percentages across countries, industries, and years. Each point encodes additional dimensions through color (regulation status), size (content volume), and position, with tooltips revealing exact values. Built with D3 v7, the visualization uses d3.csvParse for data loading, d3.scaleLinear for axes, and interactive controls for filtering by year, industry, and country. A view switcher toggles between scatter and trend representations within the same SVG-based interface.

Fork of Fork of Fork of Fork of Global AI Content Impact Dataset - Set5

This fork-of-a-fork visualization provides an interactive scatter plot of the Global AI Content Impact Dataset, showing relationships among numeric columns like AI Adoption Rate, Job Loss, and Revenue Increase, colored by categorical fields such as Country or Industry. A view switcher toggles between scatter and trends views, while dropdowns and checkboxes let users select dimensions. Built with D3 v7, it fetches CSV data, coerces values with custom parsing, and renders SVG charts with dynamic controls.

Fork of Fork of Fork of Global AI Content Impact Dataset - Set4

This interactive scatterplot explores a synthetic global AI impact dataset, plotting metrics such as AI adoption rate against AI-generated content volume. Users can change the x-axis, y-axis, and point size via dropdown controls, with points colored by country and represented as SVG circles. The visualization reads a CSV file using d3.csvParse, coerces values, and maps column names heuristically before rendering with D3 v7 scales and axes. A legend and tooltip provide additional context for each country-industry-year observation.

Fork of Fork of Global AI Content Impact Dataset - Set3

This scatterplot visualizes the relationship between AI adoption rate and AI-generated content volume across countries and industries, with point size encoding market share. Interactive dropdown menus allow filtering by year and selecting which numeric variables map to the x-axis, y-axis, and point size. The visualization is built with D3 v7 using SVG rendering, and loads data from a CSV file parsed with `d3.csvParse` or tab-delimited format detection.

Fork of Global AI Content Impact Dataset - Set2

This interactive scatterplot explores the Global AI Content Impact Dataset, filtering by year and industry to compare AI adoption rates against metrics like job loss, revenue increase, and consumer trust. The visualization uses D3 v7 to render an SVG chart, with dropdown menus controlling the year and industry filters, and additional dropdowns selecting the x- and y-axis numeric columns. Each data point is scaled by market share when selected. The code derives column names heuristically (e.g., matching “adoption” or “displacement” patterns) and coerces string values into numbers before plotting. The chart is drawn within a fixed-width container with a legend gutter on the right.

Fork of Fork of Fork of Basic Revised Scatter Plot with React & D3 using Global AI Content Data

This scatter plot visualizes the relationship between automation probability and employment numbers for various occupations in New York. Each circle represents an occupation, with position encoding automation probability on the x-axis and log-scaled employment on the y-axis, while circle size reflects the product of both values. The visualization uses React and D3 v7, employing `d3.csv` and `d3.dsv` for data loading, `scaleSqrt` for radius scaling, and `scaleLog` for the logarithmic y-axis. Labels highlight the twelve highest-impact occupations.

Fork of Fork of Basic Scatter Plot with React & D3 using Global AI Content Data

This scatter plot visualizes the probability of automation for various occupations against their employment counts in New York, using global AI content data loaded from a CSV file. Built with React and D3 v7, it renders circles scaled by a fixed radius, with axes, labels, and a linear scale for both dimensions. The app normalizes headers, parses numeric values, and filters incomplete rows before drawing, employing D3’s `scaleLinear`, `axisBottom`, `axisLeft`, and the join operator for efficient SVG updates.

Fork of Basic Scatter Plot with React & D3 using Global AI Content Data

This scatter plot visualizes the relationship between automation probability (x-axis) and New York employment counts (y-axis) for individual occupations. Built with React and D3 v7, it loads occupation data from a CSV file and renders circles for each role. The visualization uses D3’s scaleLinear for axes, axisBottom and axisLeft for ticks, and extent to compute domains. The React app handles CSV parsing and data cleaning, including normalization of headers and numeric values.

Global AI Content Impact Dataset

This scatter plot explores the relationship between AI adoption and job displacement across countries and industries, with point size encoding market share. Users can filter by year and industry, and select which quantitative attributes to plot on each axis. The visualization is implemented using D3 v7, parsing the Kaggle dataset via `d3.csvParse`, mapping columns through regex, and rendering an interactive SVG chart with select elements for controls.

Occupation, Salary, and Likelihood of Automation

AI-Powered Job Market Insights

This visualization displays the average salary for each job title in the AI-powered job market dataset, with bars sorted in descending order to reveal the highest-paying roles. Using D3 v7, the chart renders as an SVG with a band scale for the categorical job titles and a linear scale for salary values. The code fetches data from a CSV file, aggregates salaries by job title with `d3.group` and `d3.mean`, and builds the bar chart with axes, rotated labels, and formatting via `d3.axisBottom`, `d3.axisLeft`, and `tickFormat`.

Fork of Circles with D3

A set of seven semi-transparent circles, each with a distinct neon color, converges at the center of a fixed, full-viewport SVG. The circles are first sorted by descending radius so larger shapes render behind smaller ones. Using D3 v7's `select` and the `.join` operator, the visualization binds data to circle elements, setting their `cx` and `cy` attributes to the container's midpoint and their `r` and `fill` from a hardcoded data array.