Brain and CNS Cancer Mortality Rate in UK

line

This example shows the trend of brain and CNS cancer cases over time as a line chart, with data loaded from a CSV file. The visualization uses D3 v7 to create SVG-based axes with gridlines, mapping years to the x-axis and cancer case counts to the y-axis. The line generator, scales, and axis functions from D3 are used to draw the chart, while the dataset is parsed and mapped to the expected columns before rendering.

Ssaiyogesh9911@gmail.com

69% match

Tthe.purple.catfish@gmail.com

England and Wales Mortality Statistics

This visualization displays weekly total deaths across all ages in England and Wales, plotted as a single red line over time. The data is loaded from a CSV file and aggregated by date. Built with React and D3 v7, it uses `scaleTime` and `scaleLinear` for axes, `d3.line` with `curveNatural` to draw the series, and SVG rendering for the chart. Axes are generated using D3's `ticks()` method.

68% match

Fork of Cancer Survival Rates

This visualization shows a network of cancer types in the United States, with the country as a central red node connected to various blue cancer-type nodes. The code uses D3.js v6 with `d3.forceSimulation`, `d3.forceLink`, `d3.forceManyBody`, and `d3.forceCenter` to position nodes, along with `d3.drag` for interactivity. Data is loaded from a CSV file using `d3.csv` and rendered as SVG elements, with labels displaying each cancer type.

BBajiSharifPatan@my.unt.edu

Fork of D3: GeoEarth

This visualization displays global deaths from brain and central nervous system cancer for 2019, using a natural Earth projection with a sequential yellow-orange-red color scale. It shows country-level data from a CSV dataset of cancer statistics, mapped via ISO codes to world atlas geography. The code uses React to manage state, d3.geoPath and geoNaturalEarth1 for map rendering, d3.scaleSequential with interpolateYlOrRd for coloring, and topojson’s feature method to convert TopoJSON boundaries. Hovering reveals country names and death counts via a tooltip, while a legend indicates color ranges.

ICE-6 Impact of Cancer Deaths 2019

This interactive visualization displays cancer mortality trends in the United States from 1990 to 2019, plotting individual yearly death counts for fifteen distinct cancer types as colored dots. The scatterplot uses SVG circles rendered through React and D3, with each cancer type assigned a unique color and an interactive tooltip revealing exact death numbers on hover. Built with D3 scales (`scaleTime`, `scaleLinear`), axes (`axisLeft`, `axisBottom`), and event handlers, the chart reads from a CSV dataset filtered for USA records, making temporal patterns across cancer categories immediately comparable.

Tree graph of Death Rates from 10 Types of Cancer Across Various Countries

A tree graph displays hierarchical death rates for ten cancer types across countries (United States, Canada, Japan, China) for 2019. Each branch represents a country and cancer type, with leaf nodes showing the number of deaths. Using D3 v6’s `d3.tree()` layout on an SVG canvas, nodes are positioned vertically, with blue internal nodes and red leaves. The data originates from a CSV file and is structured with a parent ID function that splits the hierarchical ID string.

Vviveknaroju999@gmail.com

Fork of Fork of Fork of HTML Starter

This animated scatter plot visualizes cancer mortality rates in the U.S. from 1999 to 2019, cycling through four cancer types—Liver, Breast, Prostate, and Thyroid—using distinct D3 symbols. The chart updates every two seconds, redrawing points with a smooth transition, while the title and axes labels adapt to reflect the selected cancer type. Built with reusable D3 modules, the visualization highlights year-over-year death trends with a clean, animated design.

Cancer Survival Rates

This visualization uses overlapping semi-transparent areas to compare cancer survival rates for females and males from 1977 to 2013. The chart highlights the trend in survival percentages over time for each sex, with pink representing females and light blue representing males. The code uses D3 v5’s `scaleTime`, `scaleLinear`, `area`, and `csv` to load and parse data, then renders the areas and axes via SVG. A legend and labeled axes clarify the visualization, which sources data from the five-year cancer survival rates by sex and race.