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@ajayk1931·7 public vizzes
This visualization plots the relationship between undergraduate (bachelor’s) and graduate (master’s) earnings across various academic fields, using data from Table 5A.csv. Each circle represents a discipline, positioned by its x and y earnings values. A dashed orangered regression line is overlaid, computed via a custom linear regression function in D3 v4, with the resulting equation displayed beneath the chart. The scatterplot uses SVG circles and D3 scales and axes to map the data.
This line chart displays average income by highest education level, from elementary school through doctorate degrees, using data from the U.S. Census Bureau’s Survey of Income and Program Participation. The visualization pairs a black polyline with colored dots at each data point, making the upward trend in earnings with advanced education clear. Built with D3 v4, it uses `d3.scaleBand` for the categorical x-axis, `d3.scaleLinear` for the y-axis, and `d3.line` to generate the path, while circles are added via `enter().append("circle")`. The chart renders as SVG with axes from `d3.axisBottom` and `d3.axisLeft`.
A normalized stacked bar chart displays the percentage distribution of college degree types across four racial categories, using data from the US Census Bureau’s 2008 Survey of Income and Program Participation. Each bar represents a race, with segments for Associate’s, Bachelor’s, Master’s, Professional, and Doctorate degrees scaled to total 100%. Built with D3 v4, the chart uses `d3.stack()` with `stackOffsetExpand` for normalization, `d3.scaleBand` for the x-axis, and `d3.scaleOrdinal` with `schemeCategory10` for color encoding. An SVG render includes a legend and percentage-scaled y-axis.
This grouped bar chart compares the number of people aged 25 and over who have attained various college degrees, broken down by age brackets from 25–34 through 65 and over, using data from the US Census Bureau’s Survey of Income and Program Participation. Five education levels—from associate’s to doctorate—are shown side by side for each age group, with population counts in thousands. The visualization uses d3.csv for data loading, d3.scaleBand for x-position and grouping, d3.scaleLinear for the y-axis, and d3.scaleOrdinal with d3.schemeCategory10 for color encoding. Axes are rendered with d3.axisBottom and d3.axisLeft, and values are formatted using d3.format.
This interactive scatter plot visualizes the Iris dataset, with points colored by species. A linear regression trendline is fitted to the data and updates dynamically as users hover over or select points. The visualization uses D3 v4 with SVG rendering, displaying sepal width against sepal length for three species. Users can interact with the plot to see how the regression line adjusts when data points are excluded, providing immediate feedback on the relationship between variables and the influence of individual points on the trendline. The regression calculation and line drawing are implemented in D3, with the JSON data embedded inline.
This bar chart visualizes educational attainment across seven age groups in the United States, with each education level represented by a cluster of colored bars. The data comes from a CSV file listing population figures in thousands. Built with D3 v4, the visualization uses `d3.scaleBand` for the categorical axes, `d3.scaleLinear` for the population axis, and `d3.schemeCategory10` for bar colors. SVG rendering handles the bars, axes, and legend, while the code loads the data asynchronously via `d3.csv`.
This visualization displays the distribution of advanced degree fields using a pie chart, with each slice representing the frequency of a field in the dataset. The chart is rendered as an SVG using D3 v4, with colors assigned via `d3.scale.ordinal` and the `d3.schemeCategory20b` palette. The data comes from `adv-inc-avg.csv`, loaded through `d3.csv`, and the pie layout is generated with `d3.pie` and drawn using `d3.arc`. Slices are filled based on the field name, with white strokes separating them.