Scatter Plot

Scatter Plot

This scatter plot displays the population of the top 10 most populous countries, based on 2020 estimates from the United Nations World Population Prospects. Each circle represents a country, positioned along the y-axis by name and the x-axis by population count. The visualization utilizes D3 v6 APIs including `scaleLinear`, `scalePoint`, `axisBottom`, and `axisLeft`, rendering as SVG. Population data from a CSV file is loaded and scaled, with grid lines and axis labels formatted using D3’s `format` function.

AAnthony Ynami

Scatter Plot

This scatter plot displays the population of the top 10 most populous countries using 2018 estimates from the United Nations World Population Prospects. The visualization uses D3 v6 with SVG rendering to position circles along categorical y-axis points and a linear x-axis. It employs `d3.scaleLinear`, `d3.scalePoint`, `d3.axisLeft`, and `d3.axisBottom` to create the chart, with population values formatted from thousands to billions using `d3.format`. Background grid lines extend from both axes, and the data is loaded asynchronously via `d3.csv`.

Ddata-inside

Scatter Plot

This scatter plot displays the population of the top 10 most populous countries using 2018 estimates from the United Nations World Population Prospects. Each circle represents a country, positioned along a linear population scale and a point-based categorical scale for country names, with a bar-chart-like layout. The visualization is built with d3.csv, d3.scaleLinear, d3.scalePoint, axisBottom, and axisLeft, rendering circles as SVG elements. Population values are formatted with d3.format and converted from thousands, with axes extended by grid lines via tickSize.

MMounikaBeerelly

Scatter Plot

This scatter plot displays the top ten most populous countries based on 2018 estimates from the United Nations World Population Prospects. Each circle’s position encodes population on the x-axis and country on the y-axis, with all circles sized at a fixed radius. The visualization uses D3’s `scaleLinear` and `scalePoint` for axes, `axisBottom` and `axisLeft` for tick marks, and `format` to abbreviate population numbers. Data is loaded from a CSV file, and the rendering is done via SVG, using circles to represent data points and custom styling for text and gridlines.

Rrebeccayc

Scatter Plot

A scatter plot displays the population of the top 10 most populous countries, using 2018 estimates from the United Nations World Population Prospects 2019. Each circle’s vertical position corresponds to a country, while its horizontal position reflects population size on a linear scale. The visualization uses D3 v5’s `csv` loader, `scaleLinear`, `scalePoint`, `axisLeft`, and `axisBottom` to render SVG circles and gridlines, with tick labels formatted in billions.

AAbhijit Roy

Scatter Plot

This scatter plot displays the population of the top 10 most populous countries based on 2018 estimates from the United Nations World Population Prospects. The visualization uses a linear scale for population on the x-axis and a point scale for country names on the y-axis, with circles sized at a fixed radius of 20 pixels. D3 v5 handles the data loading through `csv()`, while `scaleLinear`, `scalePoint`, `axisBottom`, and `axisLeft` construct the chart elements. The axes are customized with formatted tick labels that convert large numbers to abbreviations, such as “B” for billion, and grid lines extend across the plot area.

Llrakla

Scatter Plot

This scatter plot displays the population of the top 10 most populous countries using data from the 2018 United Nations World Population Prospects estimate. It shows each country as a circle positioned by population on the x-axis and country name on the y-axis. The visualization uses d3.scaleLinear and d3.scalePoint for scaling, d3.axisLeft and d3.axisBottom for axes, and renders with SVG. The code also customizes axis tick formatting and removes axis domains for a cleaner appearance.

Zztawil

Scatter Plot

This scatter plot displays the population of the top 10 most populous countries using 2018 estimates from the United Nations World Population Prospects. The visualization uses D3 v5 with SVG rendering, employing `scaleLinear` for the population axis and `scalePoint` for country categories. D3 axes are customized with tick formatting that converts numbers to abbreviated units and grid lines extending across the chart. The code reads data from a CSV file and multiplies population values by 1,000 to reflect actual figures.

SSimon Pettersson