Cars Scatter Plot

Cars Scatter Plot

This interactive scatter plot displays California county data from the UCI Auto MPG dataset, plotting a selected numeric column against county names on a point scale. A dropdown menu lets users choose which variable appears on the x-axis, while circles animate into position over two seconds using staggered delays. The visualization uses d3.csv for loading, d3.scaleLinear and d3.scalePoint for scales, and d3.axisBottom/d3.axisLeft for axes, with SVG rendering and CSS-styled circles.

96% match

Cars Scatter Plot

This interactive scatter plot displays demographic and economic data for California counties from the UCI Machine Learning Repository’s Auto MPG dataset, with a dropdown menu letting users switch the x-axis variable. Built with D3 v5, it uses `scaleLinear`, `scalePoint`, and `axisBottom` for axes, and animates circles via `transition().duration()` and `delay()` when the selection changes. The SVG rendering includes a title and axis labels, with data loaded asynchronously using `csv()`.

94% match

Cars Scatter Plot

This interactive scatter plot visualizes demographic and economic data for California counties, sourced from the UCI Machine Learning Repository’s Auto MPG dataset. Users select a numeric column from a dropdown menu to update the x-axis, while counties are ordered along the y-axis using `d3.scalePoint`. The visualization uses D3 v5, rendering circles as SVG elements with a staggered 2-second transition, employing `scaleLinear`, `axisBottom`, and `axisLeft`. The code also uses `transition().duration(2000).delay()` to animate circle positions smoothly.

94% match

Cars Scatter Plot

This interactive scatter plot displays demographic and economic data for California counties, sourced from the UCI Machine Learning Repository's Auto MPG dataset. Users select a variable from a dropdown menu to control the x-axis, with counties positioned along the y-axis using a point scale. The visualization, built with D3 v5, renders animated SVG circles that transition to their positions over two seconds using `transition.attrTween`-like delays. Axes are generated with `axisBottom` and `axisLeft`, while `scaleLinear` maps numeric values and labels are formatted using `format`.

Cars Scatter Plot

This interactive scatter plot visualizes demographic data for California counties, sourced from the UCI Auto MPG dataset. A dropdown menu lets users select which attribute to plot on the x-axis, with counties listed on the y-axis. The D3 v5 code uses `scaleLinear`, `scalePoint`, and `axisBottom` to build the chart, while `transition().duration(2000).delay(i * 10)` animates circles from the center to their positions. Each circle is semi-transparent red, and axes use custom tick formatting.

Cars Scatter Plot

This scatter plot displays population data for California counties, sourced from the UCI Machine Learning Repository’s Auto MPG dataset, with counties arranged along the y-axis and total population on a linear scale. The visualization uses D3 v5 to render SVG circles, with `d3.scalePoint` for the categorical county axis and `d3.scaleLinear` for population. The code includes a dropdown menu component built with a reusable `dropdownMenu` function, and the chart shows x-axis gridlines with a custom tick format abbreviating large numbers.

Cars Scatter Plot

This interactive scatter plot visualizes automobile characteristics from the UCI Auto MPG dataset. Users select which attribute to display on the x-axis via a dropdown menu, with miles per gallon always plotted on the y-axis. The visualization uses D3 v5 with `csv`, `scaleLinear`, and `axisBottom` to render SVG circles whose opacity reveals data density. Data loading is asynchronous, and the chart re-renders whenever the selected column changes.

Jjesramyep1263

Cars Scatter Plot

A scatter plot displays demographic data for California counties from a CSV file, with a dropdown menu to select which numeric column drives the x-axis while counties appear on the y-axis. Each circle represents a county, animated with a staggered 2-second transition. The visualization uses D3 v5 with `scaleLinear`, `scalePoint`, `axisBottom`, `axisLeft`, and `transition().delay()` to move circles from the center to their final positions. Data comes from the UCI Machine Learning Repository’s Auto MPG dataset, though the plot itself shows county-level population and socioeconomic variables loaded via `d3.csv`.