Fork of Lets Make a Bar Chart with Customizable Axes

100%

Fork of Lets Make a Bar Chart with Customizable Axes

✓ Published1🌍 Public

Last edited Dec 3, 2021

Created on Dec 3, 2021

This bar chart displays the population of the ten most populous countries, using horizontal bars ordered by rank. The visualization is built with D3 v7, leveraging `d3.csv`, `scaleLinear`, and `scaleBand` to map population values and country names. Axes are customized with `axisBottom` and `axisLeft`, including formatted tick labels and gridlines, while SVG rectangles render the data in a clean, minimal layout.

AI-generated description

MIT Licensed

Similar vizzes

Loading thumbnail…

Fork of Making a Bar Chart

This example visualizes the top 10 most populous countries as a horizontal bar chart, with population values scaled linearly and sorted by descending size. The chart uses D3 v5’s `scaleLinear`, `scaleBand`, `axisLeft`, and `axisBottom` to render SVG bars and axes, while the `csv` loader imports population data from a local CSV file. Axis labels and a chart title are added via SVG text elements, and population tick labels are formatted using D3’s `format` function with abbreviations for billions.

0057SatvikDamera

92% match

Loading thumbnail…

Fork of Making a Bar Chart/Customizing Axis

A horizontal bar chart displays the ten most populous countries, with population values on the x-axis and country names on the y-axis. Population numbers are formatted using `d3.format`. The chart uses `d3.scaleLinear` and `d3.scaleBand` to map data from a CSV file, with `d3.axisLeft` and `d3.axisBottom` for the axes. SVG rectangles are rendered via D3 selections, with the y-axis domain removed and grid lines drawn through `tickSize`.

Aadelgrosso

92% match

Loading thumbnail…

Fork of Customizing Axes

This bar chart displays the top 10 most populous countries using horizontal bars, with population values on the x-axis and country names on the y-axis. The visualization uses D3 v5 with `d3.csv` to load data, `scaleLinear` and `scaleBand` for scaling, and `axisBottom` and `axisLeft` for axes. Data originates from a CSV file, rendered as SVG rectangles with custom tick formatting that converts billions to "B" notation.

WWaffleSlayer69

92% match

Loading thumbnail…

Fork of Making A Bar Chart

This bar chart displays the populations of the ten most populous countries, using horizontal bars ordered from largest to smallest. The visualization is built with D3 v7, loading data from a CSV file via `d3.csv` and rendering SVG elements. It employs `scaleLinear` for the x-axis, `scaleBand` for the categorical y-axis, and `axisLeft` and `axisBottom` to generate the axes. Each rectangle’s height is determined by the band scale’s bandwidth, and the fill color is set through CSS.

NNigel

91% match

Loading thumbnail…

Fork of Making A Bar Chart

NNigel

91% match

Loading thumbnail…

Fork of Fork of Making a Bar Chart

This visualization displays the top 10 most populous countries as a horizontal bar chart using SVG rendering. It loads population data from a CSV file via `d3.csv`, scales the values with `d3.scaleLinear` and `d3.scaleBand`, and formats axis ticks with `d3.format`. The chart uses `d3.axisLeft` and `d3.axisBottom` for axes, with custom labels and a steelblue fill for bars.

0057SatvikDamera

91% match

Loading thumbnail…

Fork of Making BarChart

This horizontal bar chart displays the population of the ten most populous countries, using a linear scale for population and a band scale for country names. Built with D3 v5, it loads data from a CSV file via `d3.csv` and renders bars as SVG rectangles. The chart includes a formatted x-axis with tick labels shortened using `d3.format`, a title, and removes redundant axis lines. Margins are applied through a transformed group element.

DDhiva21

91% match

Loading thumbnail…

Fork of Making A Bar Chart

This example displays a horizontal bar chart of population figures for the ten most populous countries, with each bar’s length proportional to its population value. The visualization uses D3 v7’s `scaleLinear` and `scaleBand` to map the data, and renders the chart as SVG elements created with `selectAll` and `enter()`. Population values are loaded from a CSV file and multiplied by 1000, with axes generated using `axisLeft` and `axisBottom`.

FFahad Bin Emran

91% match