Old Faithful HeatMap 06

Old Faithful HeatMap 07

This visualization displays the Old Faithful dataset as a grid of small multiples, each a binned heatmap that compares one of three eruption duration variables (rows) against one of six waiting time variables (columns). The code uses the Vega-Lite API to construct the repeated chart specifications, with vegaEmbed handling rendering. It computes bin counts from the data and colors rectangles by frequency using a greens scheme, drawing from a remote CSV file.

95% match

Old Faithful HeatMap 08

This example visualizes the Old Faithful dataset as a 2D heatmap, splitting the data into four facet panels based on two repeated row and column fields. Each panel displays binned counts of eruptions, with color intensity representing frequency, using a green color scheme. The visualization is built with Vega-Lite and Vega-Embed, leveraging the `repeat` operator and a `Maxbins` parameter bound to a slider for interactive bin-width control. Data is loaded from a CSV via D3’s `d3.csv`, and the chart renders as SVG with a transparent view stroke.

93% match

Old Faithful HeatMap A 03

This visualization presents the Old Faithful dataset as a binned heatmap, with eruption duration on the x-axis and waiting time on the y-axis, colored by the mean waiting time within each bin using a green color scheme. The code builds the chart through Vega-Lite’s layered API, combining rect marks for the heatmap cells and text marks to label each bin’s average value, while vegaEmbed renders the final SVG. Data is loaded via d3.tsv from the raw GitHub source, and the bin count is fixed at 10 along the horizontal axis.

93% match

Old Faithful HeatMap 10

This visualization presents the Old Faithful dataset as a 2D binned heatmap, with four panels showing combinations of the dataset’s numeric columns. A slider dynamically adjusts the maximum number of histogram bins for the x- and y-axes, while color intensity reflects the count of records per bin. Built with Vega-Lite and vega-embed, it uses a repeat operator to generate the grid and a `greens` color scheme for the heatmap. Data is loaded as CSV via d3.csv, and the visualization renders as SVG.

Old Faithful HeatMap 03

This interactive heatmap visualizes the Old Faithful dataset, showing the relationship between eruption duration and waiting time through binned rectangular cells colored by count on a green scale. Rendered as SVG via Vega-Lite’s `rect` mark, the visualization updates dynamically as the mouse moves across the page, adjusting the maximum number of bins on the x-axis based on cursor position. The code uses Vega-Embed, Vega-Lite’s API, and d3.tsv for data loading, with the view’s legend offset to the left.

Old Faithful HeatMap 05

This interactive visualization displays the Old Faithful dataset as a grid of binned scatterplots, with rows and columns representing repeated variable pairs. Each cell renders a binned heatmap using Vega-Lite’s rect mark, where color intensity reflects outlier counts. The interface responds to mouse movement, dynamically adjusting the maximum bin count via `d3.csv` loading and `vegaEmbed` re-rendering with updated specifications. The example relies on the Vega-Lite API and D3 v4 to fetch data and handle events.

Old Faithful HeatMap 09

This visualization displays the Old Faithful dataset as a binned heatmap, using a 2x2 grid of repeated charts to explore relationships between four quantitative variables. Each cell shows the count of data points within binned ranges, colored on a green scale. The code uses Vega-Lite’s `repeat` operator and `bin` encodings, with an interactive slider controlling the `Maxbins` parameter. Data is loaded from a CSV via `d3.csv`, and rendering is handled by `vegaEmbed` with Vega-Lite specifications.

Old Faithful HeatMap 04

This interactive heatmap visualizes the bivariate distribution of eruption durations and waiting times in the Old Faithful dataset, using a green color scale and rectangular bins. The visualization is built with Vega-Lite, embedded via vega-embed, and loads data asynchronously through d3.tsv. Moving the mouse updates the bin count for both axes, recomputing the entire chart in real time by calling vegaEmbed with new specifications that adjust the maximum number of bins dynamically based on cursor position.