Untitled

100%

✓ Published0🌍 Public

Last edited Mar 16, 2021

Created on Mar 15, 2021

This interactive scatterplot matrix visualizes an environmental dataset, with each cell showing the relationship between two variables such as age, income, and education. Users can brush across any axis to filter the data points, which hides or highlights circles across all cells simultaneously using a brush interaction implemented with `d3.brush`. The visualization is rendered as SVG using D3 v4 within a React framework, with axes scaled via `d3.scaleLinear` and colored by categorical country data. A legend identifies the three color-coded countries: China, Brazil, and USA.

AI-generated description

A bare minimum HTML page demonstrating use of CSS and JavaScript.

Similar vizzes

Loading thumbnail…

Untitled

This visualization presents a scatterplot matrix of environmental indicators for Brazil, China, and the USA, plotting six variables including forest cover, agriculture, and primary forest percentage. Each off-diagonal cell displays a bivariate scatterplot of two variables, colored by country, while diagonal cells show variable names. The code uses d3.brush to enable interactive filtering by dragging along any cell, which dims non-selected data points across all plots. Axes and frames are rendered via d3.axisBottom, d3.axisLeft, and SVG rect elements, with data parsed from the Env.csv file.

Mmuzzheng

86% match

Loading thumbnail…

Untitled

This example shows a scatterplot matrix comparing six environmental metrics—forest cover, agriculture, wood removal, planted forest, and primary forest—across Brazil, the USA, and China, using data from Env.csv. It displays pairwise relationships between all traits, with points colored by country and a legend identifying each nation. The visualization uses D3 v4 to render SVG shapes, scales, axes, and a brushing interaction that highlights selected data points by hiding others. Each cell is built with the `cross` function, relying on D3 scales and the `d3.brush` API for filtering.

Mmuzzheng

86% match

Loading thumbnail…

Untitled

This is a scatterplot matrix visualizing relationships among six traits from an environmental dataset, with each cell showing a plot for a pair of traits. The data points are colored by eventname using a categorical color scale, and users can click cells to filter points via a brush interaction. The visualization is built with D3 v4, using scales like `d3.scaleLinear` and `d3.scaleOrdinal`, a brush API for filtering, and SVG rendering within a React framework. The data is loaded from a CSV file, and a legend labels the three event categories.

Mmuzzheng

84% match

Loading thumbnail…

Untitled

This interactive scatter plot displays three clusters of points, colored by category, and allows users to brush a region to zoom into that area. The visualization uses D3 v4 to generate data from a normal distribution, render SVG circles, and implement brushing with `d3.brush`. Axes are drawn with `d3.axisTop` and `d3.axisRight`, and zoom animations are handled via `svg.transition()`. The code also references a `data.csv` file with population figures, though the chart itself visualizes synthetic points.

Pprincit

83% match

Loading thumbnail…

Untitled

This example uses a parallel coordinates chart to compare countries across multiple dimensions—population, surface area, and agricultural land percentage—over several decades. Grey background lines provide context, while steel blue foreground lines highlight the highlighted data points. Brushing on any axis filters the displayed lines, showing only those that meet the selected criteria. The visualization is built with D3 v3, using `d3.scale.ordinal` and `d3.scale.linear` for axes, `d3.svg.line` for paths, and `d3.svg.brush` for interactive filtering. Data is loaded from a CSV file.

Mmuzzheng

82% match

Loading thumbnail…

Untitled

This interactive scatterplot compares a selected social indicator against age-standardized depression rates across countries, with each circle representing a year's data for a chosen region. Users can switch the x-axis between Freedom, Corruption, Generosity, and Health, and filter by geographic region via dropdown menus. Built with React and D3 v6, the visualization uses `d3.scaleLinear`, `d3.axisBottom`, and `d3.axisLeft` to render SVG circles, with a color-coded legend distinguishing years. Data comes from the `data.csv` file, and the title suggests a thematic focus on societal factors versus depression.

NNikithakatta30

79% match

Loading thumbnail…

Untitled

This interactive scatterplot explores the relationship between a selectable metric (Freedom, Corruption, Generosity, or Health) and depression rates across all ages, filtered by world region. Colored dots represent different years, with tooltips revealing exact values. The visualization uses D3 v6 to load CSV data via `d3.csvParse`, render SVG elements, and update scales, axes, and circles dynamically through dropdown selectors.

NNikithakatta30

78% match

Loading thumbnail…

Untitled

This interactive scatterplot explores yearly changes across seven data categories (A–G), displaying each category as a dot plotted along an ordinal x-axis of bars. Users navigate between years with left and right arrow keys, with an automatic playback feature advancing through the dataset. Built with React and D3.js v3, the visualization uses SVG rendering with `d3.scale.ordinal`, `d3.svg.axis`, and `d3.scale.category10` for color encoding. Data loads from an external CSV file, and the chart includes keyboard event handling and dynamic axis updates.

TThandolwethu Shakes Dlamini

78% match