Fork of React & D3 Starter

100%

Fork of React & D3 Starter

✓ Published1🌍 Public

Last edited Nov 1, 2022

Created on Nov 1, 2022

This example shows a scatter plot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis, with each circle representing a flower sample. The visualization is built with React and D3 v7, using a custom `viz` function that creates linear scales via `d3.scaleLinear` and renders SVG circles with the data join pattern. Axes are added through `d3.axisLeft` and `d3.axisBottom` in a separate module. The code demonstrates a decoupled architecture where React manages the component lifecycle and D3 handles the drawing logic, with data loaded asynchronously via `d3.csv`.

AI-generated description

This viz is a starter that demonstrates patterns used in real world projects in which complexity is anticipated to scale.

Decoupled React & D3 integration
Opening moves for scalable complexity
Industry standard ES modules and JSX
Copy-paste into existing projects

Any questions? Ask on Twitter!

Also viewable in:

MIT Licensed

Similar vizzes

Loading thumbnail…

Fork of React & D3 Starter

This example presents a scatter plot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis. It demonstrates a decoupled React and D3 integration pattern for scalable projects, rendering circles as SVG elements within a React component. The code uses D3’s `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` for scales and axes, while React manages component state and lifecycle. Data is loaded asynchronously from a CSV file using D3’s `csv` function, with the visualization wrapped in a reusable `viz` function.

Ccm

97% match

Loading thumbnail…

Fork of React & D3 Starter

This example shows a scatterplot of the Iris dataset, plotting sepal length against petal length for each flower sample. The visualization is built with React and D3 v7, where React manages the component lifecycle and D3 handles the rendering of circles, axes, and scales. The visualization uses D3's `csv` loader to parse the data, `scaleLinear` for coordinate mapping, and `axisLeft`/`axisBottom` for the axes, all output as SVG elements.

SSimone Tolomelli

96% match

Loading thumbnail…

Fork of React & D3 Starter

This example demonstrates a scatter plot of the Iris dataset, mapping sepal length on the x-axis and petal length on the y-axis, with circles colored by species. The visualization is built with React and D3 v7, using a decoupled architecture where React manages the SVG container and D3 handles scales, axes, and circle rendering via `d3.axisLeft`, `d3.axisBottom`, `d3.scaleLinear`, and `d3.extent`. Data is loaded asynchronously from a CSV file using `d3.csv`.

GGuna

96% match

Loading thumbnail…

Fork of React & D3 Starter

This example demonstrates a scatter plot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis. The visualization uses a decoupled React and D3 integration, where a React component manages the SVG element while D3’s `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` handle scaling and axes. Data is loaded asynchronously via `d3.csv` and parsed into numeric values. The code showcases reusable patterns for scalable projects, rendering circles with a fill opacity of 0.5 across the full browser window.

Sshivendrarai

96% match

Loading thumbnail…

Fork of Fork of React & D3 Starter-2

This example displays a scatterplot of the classic Iris flower dataset, using sepal length for the x-axis and petal length for the y-axis, with each point drawn as a semi-transparent circle. The visualization is implemented using React for the component structure and D3 v7 for the rendering logic, specifically leveraging D3's `scaleLinear`, `extent`, and axis functions to map data values to pixel coordinates. The SVG output is generated within a React wrapper that uses a `useRef` hook to pass the target element to the D3 visualization function. The data is loaded asynchronously via D3's `csv` parser, and the chart scales to the full size of the browser window.

RROU

96% match

Loading thumbnail…

Fork of Fork of React & D3 Starter

This example demonstrates a React and D3 starter template for building scalable data visualizations with decoupled integration. It displays a scatterplot of flower measurements from the classic Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis using `d3.scaleLinear` and `d3.extent`. Circles represent individual data points, with axes generated via `d3.axisLeft` and `d3.axisBottom`. The visualization uses React versions 18.1.0 and D3 version 7.4.4, rendering in SVG. The architecture separates React components from D3 logic, showcasing patterns for handling complexity as projects grow.

CCheng Tang

95% match

Loading thumbnail…

Fork of React & D3 Starter

This example demonstrates a scatterplot of the Iris dataset, plotting sepal length against petal length as semi-transparent circles rendered in SVG. It uses React to manage the component lifecycle, with a `useData` hook loading CSV data via `d3.csv` and a `VizWrapper` component using `useEffect` and `select` to invoke the D3 `viz` function. D3 scales (`scaleLinear`, `extent`) and axes (`axisLeft`, `axisBottom`) are employed, showcasing a decoupled React and D3 integration pattern for scalable projects.

SSofia Nagavkina

95% match

Loading thumbnail…

Fork of React & D3 Starter

This example shows a scatterplot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis, with semi-transparent circles for each observation. It demonstrates a pattern for integrating React and D3.js, where React manages the component lifecycle and DOM rendering via JSX, while D3 handles scales, axes, and the data join. The visualization uses `d3.scaleLinear` for both axes, `d3.extent` to compute domains, and `d3.axisLeft` and `d3.axisBottom` to draw the axes. The code is structured as a starter template, separating data loading, viz logic, and React wrappers for scalable complexity.

IIndhuKrishnaraj

95% match