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Vveagy
Last edited Oct 7, 2018
Created on Oct 7, 2018
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This scatter plot visualizes annual export values from 2000 to 2016, comparing shipments to the United States against those to China, with each point representing a country-year observation. The chart uses D3 v5's `scaleLinear`, `axisLeft`, and `axisBottom` to construct axes with abbreviated number formatting, while circles are rendered via SVG. Data comes from a CSV file loaded with `d3.csv`, and the code explicitly converts six country columns to numeric values before plotting. Red, semi-transparent circles reveal overlapping data density, with labeled axes and a title indicating the export comparison.

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This scatter plot shows data about cars, from UCI Machine Learning Repository: Auto MPG Data Set.

MIT Licensed

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This scatter plot visualizes worldwide export values to the United States and China from 2000 to 2016, with each circle representing a country’s annual exports. The data comes from a CSV file loaded via `d3.csv`, and the chart uses `d3.scaleLinear`, `d3.axisLeft`, and `d3.axisBottom` to render axes with abbreviated tick labels. Circles are drawn as SVG elements with a fixed radius, while axis labels and the title are added as SVG text. The visualization shows the relationship between exports to the two major economies, with overlapping red circles indicating similar values.

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This scatter plot visualizes worldwide export values to the United States and China from 2000–2016, with each circle’s color encoding the export indicator category. A legend identifies the categories, and axis labels clarify the compared countries. Built with d3.csv, d3.scaleLinear, d3.axisBottom, d3.axisLeft, and d3.scaleOrdinal, the SVG renders points with a categorical color scheme. Data is loaded from a hosted CSV file, and circles use fixed opacity for overlapping points.

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A scatterplot compares export values to the United States versus China using a CSV dataset of worldwide exports from 2000–2016. Each circle’s color encodes an indicator description via d3.scaleOrdinal with schemeCategory10, with a legend and linear axes formatted using d3.format. The visualization is rendered as an SVG using d3.select, d3.scaleLinear, d3.extent, d3.axisLeft, and d3.axisBottom, with a title and labeled axes.

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This scatterplot visualizes worldwide export values to the United States and China, with each circle colored by indicator type. The chart uses D3 v5 scales and axes, including `scaleLinear`, `scaleOrdinal`, `axisLeft`, and `axisBottom`, to position points and format tick labels with `format(".2s")`. Data is loaded from a CSV file via the `csv` function, and circles are rendered as SVG elements with a legend built using `color.domain()`. The y-axis and x-axis labels identify the two destination countries, while a title summarizes the comparison.

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This scatterplot shows the relationship between exports to the United States and exports to China for various countries from 2000 to 2016, based on World Trade Organization data. Each circle represents a country, colored by its indicator description, with axes labeled for the two destinations. The visualization uses D3 v5’s `scaleLinear`, `axisLeft`, `axisBottom`, and `scaleOrdinal` with `schemeCategory10`, rendering as SVG. Data is loaded via `d3.csv` and formatted with `format(".2s")`, while a legend identifies the color-coded categories.

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This scatter plot visualizes worldwide export values to the United States versus China from 2000–2016, with each circle representing a yearly observation. The animation transitions circles from radius zero to their final size using chained `transition().duration()` and `delay()` calls. Built with D3 v5, the example uses `scaleLinear`, `axisLeft`, and `axisBottom` to construct axes, alongside `csv()` to load the dataset from VizHub. SVG rendering displays the data, with tick marks and gridlines styled via CSS classes.

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This scatter plot visualizes worldwide export values to the United States and China, with each circle colored by its indicator category. A legend identifies the categories. The visualization uses d3.csv to load the dataset and d3.scaleLinear, d3.axisBottom, d3.axisLeft, and d3.scaleOrdinal with schemeCategory10 for encoding. The SVG rendering includes axis labels, a title, and grid lines via tickSize, with legends positioned using SVG groups and rectangles.

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