Scatter plot

This scatter plot shows the population of the top 10 most populous countries, with each circle positioned along a linear population scale and a point scale for country names. The visualization uses d3.csv to load data, d3.scaleLinear and d3.scalePoint for axes, and d3.axisLeft and d3.axisBottom with customized tick formatting that abbreviates billions as "B." Circles are rendered as SVG elements with a fixed radius, while grid lines and axis labels are styled via CSS.

Nnick-yadav

Scatter Plot

This scatter plot displays the population of the top 10 most populous countries, with circles positioned along a linear x-axis for population and a point-based y-axis for country names. The visualization uses d3.csv to load the data, d3.scaleLinear and d3.scalePoint for scaling, and d3.axisBottom and d3.axisLeft for axes, rendered as SVG circles with a steelblue fill. Grid lines are drawn via tick sizes, and the x-axis labels are formatted using d3.format.

Nntds12

Scatter Plot

This scatter plot visualizes the population of the top 10 most populous countries, with each circle’s horizontal position encoding population and vertical position encoding country name. It uses d3.scaleLinear for the x-axis, d3.scalePoint for the y-axis, and d3.axisBottom and d3.axisLeft for ticks. Data is loaded from a CSV and formatted with d3.format, rendering as SVG circles within styled axes and a title.

CCatriona

Scatter Plot

This scatter plot displays the top 10 most populous countries, using circles positioned along a linear population scale and a point-based country axis. The visualization encodes each nation’s population with a circle’s horizontal placement, while vertical positioning separates countries for readability. The code leverages d3.csv for data loading, d3.scaleLinear and d3.scalePoint for scaling, and d3.axisLeft and d3.axisBottom to render labeled axes. Population values from the data file are multiplied by 1,000 and formatted with d3.format, with the SVG output styled using CSS.

Iisaachowen

Scatter Plot

This scatter plot displays the top 10 most populous countries, with each country’s population plotted along the horizontal axis and its name along the vertical axis. The visualization uses D3 v6 with an SVG rendering approach, leveraging `scaleLinear` and `scalePoint` for axes, and `csv` to load population data from `data.csv`. The chart includes custom tick formatting via `format('.3s')` and styled grid lines, with circles colored steelblue on a yellow background.

Ssmosgasbord

Scatter Plot

This scatter plot displays the population of the top 10 most populous countries, using a linear scale for population and a point scale for country names. The visualization employs D3 v5 APIs including `scaleLinear`, `scalePoint`, `axisBottom`, and `axisLeft`, rendering SVG circles with fixed radii. Data is loaded from a CSV file with d3.csv, and population values are converted to numbers and multiplied by 1000. The chart includes formatted axis tick labels using d3.format’s `.3s` notation and gridlines via negative tick sizes.

Aandy-yc-lin

Scatter Plot

This scatter plot displays the top 10 most populous countries, with population on the x-axis and country names on the y-axis. It uses d3.csv to load the data and d3.scaleLinear and d3.scalePoint for positioning, while d3.axisBottom and d3.axisLeft render the axes with tick lines. The circles are drawn as SVG elements, and the population values are formatted using d3.format with a custom tick format that converts billions from 'G' to 'B'. The chart includes axis labels and a title, all styled via CSS.

EErik Rudhe

Scatter plot

A scatter plot displays the population of the top 10 most populous countries, with circles positioned along a linear population scale and a point scale for country names. The visualization uses d3.csv to load data, d3.scaleLinear for the x-axis, d3.scalePoint for the y-axis, and d3.axisBottom with a custom tick format converting G to B. Circles appear with a 1000ms d3.transition using easeLinear, rendered as SVG elements with steelblue-to-gray color scaling based on population values.

CChris Mora