D3 Scatterplot Example

Cars Scatter Plot

This scatter plot visualizes car data from the UCI Machine Learning Repository’s Auto MPG dataset, displayed as red semi-transparent circles on an SVG canvas. The chart maps quantitative attributes to the x- and y-axes using D3 v5’s `scaleLinear`, `extent`, and `axisBottom`/`axisLeft` functions, with labeled tick marks and an axis label. Data is loaded via `d3.csv` and rendered with `select` and `svg` elements, styled through CSS for opacity and typography. The code sets a fixed 960×500 pixel SVG and uses only the imported D3 modules for scaling and axes.

91% match

Cars Scatter Plot

This scatter plot visualizes automobile data from the UCI Machine Learning Repository’s Auto MPG dataset, displaying relationships between vehicle attributes. Built with D3 v5, the SVG-based visualization uses `d3.scaleLinear` for axes and `d3.scaleOrdinal` for color encoding. The code renders grouped bar charts from CSV data rather than traditional scatter points, with `d3.scaleBand` handling categorical month groupings and `d3.axisLeft` and `d3.axisBottom` constructing the chart’s axes.

91% match

Cars Scatter Plot

This scatter plot displays automobile data from the UCI Machine Learning Repository's Auto MPG data set. The visualization uses D3 version 5 to render SVG circles, with a red, semi-transparent fill, within a fixed 960×500 pixel canvas. The code defines linear scales for both axes, though the current implementation only maps population data from a separate CSV file, which is not the car data mentioned in the title. Axis labels and ticks are styled via CSS, and a title is included, though the visualization appears incomplete.

91% match

Cars Scatter Plot

This scatter plot visualizes car data from the UCI Machine Learning Repository’s Auto MPG dataset. It renders circular points on an SVG canvas, with each circle representing a car’s attributes. The code uses d3.scaleLinear for the x-axis population scale and d3.scaleBand for the y-axis, though the scatter point mapping is incomplete in the provided source. Axes are drawn with d3.axisLeft and d3.axisBottom, while d3.csv loads the data. The visualization appears interactive only through its static SVG rendering, with styling handled by external CSS.

The d3 test

This scatter plot visualizes car data from the UCI Machine Learning Repository’s Auto MPG dataset. It uses d3.v2 to render circles representing individual cars, with styling defined by CSS. The chart displays the relationship between variables through a simple scatter layout, using d3’s basic selection and data-binding methods. The axis labels and title are formatted with custom font sizes, and the SVG update pattern is handled within the d3 framework.

SSushanta77

Cars Scatter Plot

This scatter plot visualizes car data from the UCI Machine Learning Repository's Auto MPG Data Set, showing the relationship between vehicle attributes. The visualization uses D3.js version 5 with an SVG rendering approach, employing `d3.scaleLinear`, `d3.scaleBand`, and `d3.scaleOrdinal` to map the data. The code reads data from a CSV file and creates grouped bar charts for each month, with colors distinguishing different telescope measurements. Axes are rendered using `axisLeft` and `axisBottom` functions, with styling applied through a linked CSS file.

Cars Scatter Plot

This scatter plot visualizes car data from the UCI Machine Learning Repository’s Auto MPG dataset. It uses d3.scaleLinear and d3.scaleBand to map continuous and categorical variables, with SVG rectangles representing data points. The code loads a CSV file via d3.csv and processes population values, though the visualization itself displays car attributes. Axes are rendered using d3.axisLeft and d3.axisBottom, with styles defined for tick labels and the chart title.

Cars Scatter Plot

This scatter plot visualizes car data from the UCI Machine Learning Repository's Auto MPG dataset, using a D3.js SVG rendering. The code reads a CSV file containing monthly measurements for three subgroups (Lesedi, meter1, meter2) and displays them as grouped bars. It leverages `d3.scaleBand` for the categorical month axis and `d3.scaleLinear` for the value axis, with `d3.axisBottom` and `d3.axisLeft` generating the axes. A `d3.scaleOrdinal` color scale distinguishes the subgroups, which are plotted using SVG `rect` elements.