Making a Scatter Plot

Making a Scatter Plot

This example renders the Iris dataset as a scatter plot using React components and D3 scales. The visualization displays sepal width on the x-axis and sepal length on the y-axis, with each data point represented as a rectangle mark. The code constructs axes using D3’s `scaleBand` and `scaleLinear`, formats tick labels with `format`, and loads data via D3’s `csv` utility. SVG rendering is handled through React, with styling applied via CSS classes.

CCHOI SEUNG HYUN

Making a Scatter Plot

This example shows a scatter plot of the Iris dataset, mapping petal length on the x-axis and sepal width on the y-axis. The visualization includes labeled axes, tick marks, and circular marks with hover tooltips. Built with React and D3 v7, it uses `scaleLinear` and `extent` for scaling, and custom components for axes and marks that render SVG elements. Data is loaded asynchronously via `d3.csv` and parsed into numeric values.

ZZoe Ferencova

Making a Scatter plot

This example shows an interactive scatter plot of Iris flower measurements, plotting petal length along the x-axis against sepal width on the y-axis. The visualization uses React components to render SVG elements, with D3 v5 handling data loading via `d3.csv` and scales through `d3.scaleLinear` and `d3.extent`. Data comes from the Iris dataset fetched from a GitHub gist. Axes are built from custom React components that map D3 scales to SVG tick marks and labels, while each data point is rendered as a circle with a tooltip showing the formatted petal length.

SShanmukh

Scatter Plot

This scatter plot visualizes the Iris dataset, mapping sepal length on the x-axis against sepal width on the y-axis for individual flower specimens. The visualization uses React with d3.scaleLinear scales and SVG rendering, with axes generated by custom React components. Data is loaded asynchronously from a CSV file using d3.csv, with string values parsed into numbers. The plot includes formatted tick labels, axis titles, and tooltips on each circle via SVG title elements, all styled with Poppins font and subtle gray colors.

Iiblub

Scatter plot

A scatter plot displays the relationship between sepal length and sepal width for iris flowers, with each circle representing a data point. The visualization uses React for component structure and D3.js scales, ticks, and formatting to map the CSV data to SVG circles. The chart includes labeled axes for both quantitative variables, with a custom tick format replacing 'G' with 'B' for billions. The code loads data from a remote CSV using d3.csv and renders all marks as fixed-radius circles within a 1060x500 SVG canvas.

AArchit Bhargava

Scatter Plot

This scatter plot visualizes the Iris Dataset, mapping sepal length and width for individual flowers. The visualization uses React with D3 v5 scales and SVG rendering, with axes created by custom components. Data loads asynchronously via `d3.csv` and converts string values to numbers. Circles represent data points, and hovering reveals tooltips through SVG title elements, while axis tick formatting utilizes `d3.format` for compact notation.

Rrstrauss127

Scatter Plot

This scatter plot visualizes the Iris Dataset, plotting sepal length on the x-axis against sepal width on the y-axis. The React application loads the CSV data via `d3.csv` and renders the chart as an SVG. It uses D3 v5 scales (`d3.scaleLinear`) and extent to compute axes, with tick marks styled via CSS. Hovering over a circle reveals its sepal length using an SVG `<title>` tooltip.

Vvmonney

Scatter Plot

This scatter plot visualizes the Iris dataset, displaying sepal length on the x-axis and sepal width on the y-axis. Each circle represents a flower specimen, with hover tooltips revealing the exact sepal length value. The visualization uses React to render SVG elements, with D3.js functions like `scaleLinear`, `extent`, and `format` for scaling and tick formatting. The data is loaded asynchronously from a CSV file via D3's `csv` method, and custom components `AxisBottom`, `AxisLeft`, and `Marks` structure the chart.

OOm Kakatkar