rao

rao

This pie chart displays mortality rates across United States, with each slice representing a state and its corresponding death count. Built with D3 v5, the visualization uses `d3.pie` and `d3.arc` to generate the slices, while `d3.scaleOrdinal` maps state names to a predefined color palette. Death data is loaded asynchronously from a CSV file via `d3.csv`, with values parsed as numbers. A legend, constructed with SVG groups and rectangles, lists each state’s name and its death count, formatted using `d3.format`.

96% match

rao

This pie chart displays mortality rates across United States, with each slice representing a state and its corresponding death count. The visualization uses D3 v5’s `pie()` and `arc()` functions to generate the chart, with `scaleOrdinal` assigning colors to each segment. A legend on the right shows state names and formatted death values via `d3.format`. Data is loaded asynchronously from a CSV file using `d3.csv`, and the SVG rendering includes percentage-aligned labels positioned through `arc.centroid()`.

96% match

rao

A pie chart displays the top 10 countries by air pollution deaths in 2020, with each slice labeled in thousands and accompanied by a legend listing country names and values. The visualization uses d3.pie and d3.arc to generate the chart geometry, while d3.scaleOrdinal maps a fixed color palette to data segments, and d3.format handles tick label formatting. Data is loaded asynchronously via d3.csv from a GitHub gist, with the SVG rendered entirely through D3 v5’s selection and enter/exit methods.

86% match

rao

A pie chart displays the top 10 countries by air-pollution-related deaths in 2020, with each segment labeled in thousands and a legend listing countries and values. The chart is rendered in SVG using D3 v5, fetching CSV data from a GitHub gist. It uses `d3.pie` and `d3.arc` for segment geometry, `d3.scaleOrdinal` for colors, and `d3.format` to abbreviate numbers. Text labels are positioned via `arc.centroid()`, while the legend uses appended rectangles and text elements.

85% match

rao

This example visualizes the top 20 most populous countries ranked by deaths in India, using a horizontal bar chart. The chart displays each year on the y-axis and the corresponding death count on the x-axis, with bars sized proportionally to the data values. It uses D3 v5’s `scaleBand` for the categorical year axis, `scaleLinear` for the numeric scale, and React for rendering SVG elements. Data is loaded asynchronously via `d3.csv` from an external URL, and axes are drawn manually with SVG `line` and `text` elements.

rao

This example displays a horizontal bar chart of the top 10 most populous countries, ranking them by the number of deaths in India. The visualization uses React to manage state and render the SVG, while D3 v5 handles data loading, scales, and axes. The code fetches data from a CSV file using `d3.csv`, then applies `scaleBand` for the categorical country axis and `scaleLinear` for the numeric death count axis, drawing rectangles for each bar.

Pie Chart

This pie chart visualizes mortality rates across U.S. states, with each slice sized by the number of deaths and labeled with a value. The chart is rendered as an SVG using D3 v5, employing `d3.pie` and `d3.arc` to generate the segments and centroids for text placement. A legend on the right maps each color to its state and death count, with data fetched from a CSV via `d3.csv`. The visualization uses a custom color scale (`scaleOrdinal`) and formats death numbers with `d3.format`.

Ttarungunda

Fork of Pie Chart

This example visualizes mortality rates across U.S. states as an annotated pie chart, with each slice labeled and accompanied by a legend showing state names and death counts. The visualization uses D3 v5 (d3.pie, d3.arc, d3.scaleOrdinal) to generate SVG paths and text elements, pulling data from a remote CSV file. It applies a custom color scale to distinguish slices and renders the chart centered on an SVG canvas with a static legend to the right.

RRahulSai05