Fork of React & D3 Starter

Fork of React & D3 Starter

This example builds a reusable scatter plot comparing monthly Sales and Profit metrics from a CSV dataset. The chart displays eight data points as steelblue circles, with an x-axis for Sales and a y-axis for Profit, using a linear scale for both dimensions. The code leverages D3 v7’s `d3.csv` for data loading, `d3.scaleLinear` for scaling, and `d3.axisBottom`/`d3.axisLeft` for axes. A custom `scatterPlot` function encapsulates the chart logic, allowing flexible reuse with different data mappings and labels, rendered as an SVG.

86% match

Fork of React & D3 Starter

This example shows a reusable scatter plot of monthly sales versus profit from a small CSV dataset. The chart renders as SVG circles on linear x- and y-axes, with labeled axes and a title. The code defines a `scatterPlot` function that takes data and scales as props, using `d3.csv` to load the data and `d3.axisBottom` and `d3.axisLeft` to draw the axes. Color is fixed to steelblue, and the plot is built within a React JSX file.

86% match

Fork of Scatter Plot

This fork of a scatter plot visualizes monthly sales versus profit from a small CSV dataset, encoding each month as a steelblue circle. Using D3 v7 within a React framework, the code loads the data and renders the chart as an SVG, leveraging `d3.scaleLinear` and `d3.extent` to map values, and `d3.axisBottom` and `d3.axisLeft` to generate axes. The example demonstrates a reusable chart structure with configurable margins and an explicit SVG container.

83% match

SSanjayRamaSwamyAdla@my.unt.edu

Fork of Fork of Fork of Fork of Fork of React & D3 Starter

This example shows a reusable scatter plot of study hours versus test scores, with seven data points plotted on a fixed 500×400 SVG canvas. The code uses D3 v7 to create linear scales for both axes, append circles with steelblue fill, and render axis ticks via `d3.axisBottom` and `d3.axisLeft`. It also adds text labels for both axes. The visualization is implemented as a plain JavaScript function called `scatterPlot(container, data)`, which appends the SVG dynamically, while the included React starter demonstrates D3 selection in a `useEffect` hook. The dataset is hardcoded inline.

83% match

Fork of Fork of Fork of Reusable D3 Scatter Plot

This fork of a reusable D3 scatter plot displays sales data over time, with a line connecting red circular markers on a steelblue stroke. The code uses the D3.js v6 API, including `d3.csv`, `d3.scaleLinear`, `d3.extent`, `d3.axisBottom`, `d3.axisLeft`, and `d3.line`, to load CSV data and render an SVG. It includes axis labels and a custom Share Tech font. A separate `scatterPlot.js` module defines a reusable chart function with setters for configuration.

HHariniPotla@my.unt.edu

Fork of React & D3 Starter

This example shows a line chart of monthly sales figures using an SVG rendered with D3 v7. The visualization plots sales data from a CSV file, adding red circular markers for each data point and a green line to connect them. The code uses D3’s `scalePoint` and `scaleLinear` for axes, `line` for the path, `axisBottom` and `axisLeft` for ticks, and `csv` to load the data.

Fork of React & D3 Starter

This chart displays monthly sales data from a CSV file as a light-blue area chart with a blue line overlay, using an SVG rendered in D3 v7 within a static HTML page. The x-axis uses a point scale for months, while the y-axis employs a linear scale for sales values. The code constructs the chart with `d3.area` and `d3.line` generators, and configures axes using `d3.axisBottom` and `d3.axisLeft`. It reads the data asynchronously with `d3.csv`, then applies margins and transforms to position the visualization.

Fork of React & D3 Starter

A simple scatter plot displays ten labeled points from a small CSV dataset, mapping x and y coordinates with linear scales. The visualization demonstrates a modular React and D3 integration where React manages the SVG container and D3 handles the rendering logic. The `viz.js` module uses `d3.scaleLinear` and `d3.extent` to compute scales, while `axes.js` employs `d3.axisLeft` and `d3.axisBottom` for chart axes. Data flows through a custom `useData` hook that loads and parses the CSV with `d3.csv`. The code separates concerns across files, making it a practical starting template for scalable projects.

Tteissierducros