Skip to main content
100%

Weekly Patient Volume

✓ Published0🌍 Public
SSladav
Last edited Dec 2, 2016
Created on Dec 2, 2016

The interactive visualization shows weekly patient volume as a dot plot, with individual dots representing patients. Users can filter the displayed data by cancer type and treatment modality through two sets of toggle buttons, each with clear and reset options. Built with D3.js v3, it renders the plot as SVG and updates it with animated transitions. The page also includes a tabbed interface linking to the original data visualization, and uses Bootstrap for layout styling.

AI-generated description

Built with blockbuilder.org

mit Licensed

Similar vizzes

Loading thumbnail…

Fork of Reusable D3 Scatter Plot

This animated scatter plot cycles through cancer incidence data from the U.S., visualizing death rates for liver, breast, prostate, and thyroid cancers over time. Using D3 v3, it maps years to the x-axis and population to the y-axis, with each cancer type distinguished by a unique symbol (star, square, circle). The chart updates every two seconds, transitioning smoothly between datasets while rotating through the cancer types, with a title indicating the current type. Built as a reusable module, it demonstrates animated transitions, SVG rendering, and dynamic symbol mapping in a clean, informative design.

AArun
70% match
Loading thumbnail…

Reusable D3 Scatter Plot

This interactive scatter plot visualizes cancer mortality trends in the USA, cycling through liver, breast, and prostate cancer datasets. Built with D3 v6 as a reusable chart, it animates between cancer types every 3 seconds, updating the y-axis and point symbols (star, square, circle) accordingly. The chart leverages SVG rendering and custom symbol mappings to distinguish cancer types, with axes and margins configured for readability.

Bbhavana.bayyapu@gmail.com
69% match
Loading thumbnail…

AreaChart

This interactive area chart displays frequency distributions for numeric variables from a cancer diagnostic dataset using a dropdown selector. The visualization uses D3.js v6 to generate SVG paths, with `d3.bin()` creating histogram bins and `d3.area()` rendering the smoothed area shape. Users can switch between variables, triggering axis updates and chart redraws via D3’s event handling. Data is loaded remotely from a CSV file hosted on GitHub.

Jjtulasi05@gmail.com
69% match
Loading thumbnail…

Kankerscatter

A responsive scatterplot visualizes cancer prevalence (x-axis) and survival rates (y-axis) for 19 cancer types, with each type represented as two connected points (male and female). Users toggle between a full view of all cancers and a zoomed-in view focusing on rarer types. The visualization uses a D3.js SVG pipeline, with `d3.scale.linear` axes, `d3.svg.axis` for ticks, and `d3.tip` for interactive tooltips. Data comes from a local CSV (`cancerdata.csv`) and animations are handled through D3’s enter/exit transitions. The layout is generated from an SVG block with buttons controlling the zoom state.

AAndresAnayaIsaza
68% match
Loading thumbnail…

Kankerscatter

A responsive scatterplot visualizes cancer prevalence (x-axis) and survival rates (y-axis) for 19 cancer types, with each type represented as two connected points (male and female). Users toggle between a full view of all cancers and a zoomed-in view focusing on rarer types. The visualization uses a D3.js SVG pipeline, with `d3.scale.linear` axes, `d3.svg.axis` for ticks, and `d3.tip` for interactive tooltips. Data comes from a local CSV (`cancerdata.csv`) and animations are handled through D3’s enter/exit transitions. The layout is generated from an SVG block with buttons controlling the zoom state.

AAndresAnayaIsaza
68% match
Loading thumbnail…

Cancer Paitents

This visualization displays cancer patient numbers across Indian states and union territories for the year 2016, using a bar chart rendered with SVG. The React component loads data from a CSV file via `d3.csv` and maps each state to a rectangle using `scaleBand` for the y-axis and `scaleLinear` for the x-axis. The chart is built with D3 v6 and React 17, with bars positioned starting from the left edge of the SVG canvas.

Yyastika
68% match
Loading thumbnail…

Reusable D3 Scatter Plot

This animated scatter plot cycles through cancer types—liver, breast, prostate, and thyroid—displaying death rates over time using the Iris Dataset-inspired structure. Built with reusable D3.js components and SVG rendering, the visualization updates every 2 seconds, transitioning between datasets while updating the title and axis labels. Symbols vary by cancer type (circle, square, star) and axes represent years and number of deaths, with smooth transitions on each refresh.

AAsrar Al Qassem
68% match
Loading thumbnail…

Activity7_Q1

This example presents an animated visualization of the Wisconsin Breast Cancer dataset, rotating through three pie charts every few seconds. The charts display the distribution of mean smoothness, the count of malignant versus benign tumors, and the distribution of mean radius. Using D3 version 6, the visualization loads CSV data from a Gist URL, computes bin counts client-side, and renders each chart with SVG paths via d3.pie and d3.arc. A setInterval timer drives the rotation, while a legend with color-coded ranges updates for each chart.

Rrohitpotluri@my.unt.edu
68% match