drawing squares

rectangles using d3

Five rectangles are displayed in an SVG canvas. The rectangles are initially unstyled, and user interaction changes their fill color: clicking turns a rectangle orange, mouseover turns it green, and mouseenter turns it white. The code uses D3 v7's `selectAll` and `select` functions to bind event listeners and set attributes like width, height, x, and y. Positioning is computed with a conditional expression that alternates the horizontal offset based on each rectangle's index.

HHeet Bhatt

Rectangles using data

This example shows how to bind a hardcoded JSON dataset of four rectangles—each with position, size, color, and a name—to SVG elements using D3 v4. It first creates the rectangles via `d3.selectAll("rect").data(...).enter().append("rect")`, then sets their `x`, `y`, `width`, and `height` attributes and `fill` style from the data. It also appends text labels next to each rectangle, positioning them relative to the rectangle’s coordinates and size. The visualization demonstrates basic data joins and attribute binding in D3, with the source data defined inline in the script.

D3 Rectangle Examples

This example demonstrates the creation of six SVG rectangles using D3.js, each illustrating different visual properties such as fill color, stroke width and alignment, offset positioning, and corner radii. It also includes a seventh set that arranges three colored rectangles with varied dimensions and placements. The code uses D3’s selection and append methods to build SVG elements, with data defined as inline JavaScript objects specifying attributes like width, height, and style. The page is rendered at a fixed size and relies on D3 2.4.5.

GGuerino1

scale svg

This example demonstrates how to create a responsive SVG visualization using D3 v7. It displays five small rectangles positioned horizontally within a 400x400 viewBox, with each rectangle’s x-coordinate determined by its data value. The code uses `d3.select` to append an SVG element and applies the `viewBox` and `preserveAspectRatio` attributes to ensure the graphic scales proportionally to its container. The rectangles are bound to the array `[1,2,3,4,5]` using D3’s data join pattern with `selectAll`, `data`, and `enter`.

Yyar

Rectangles using data Color II

This example shows seven rectangles, each filled with a distinct color from a hardcoded JSON dataset that defines their position, size, color, and name. The rectangles are rendered on a 960 by 500 pixel SVG canvas, with each rectangle labeled next to it using its corresponding name. The code uses D3 v4’s selection and data binding to append a group for each data element, then appends a `rect` and a `text` child to each group. The rectangles use a black stroke for clarity, while the text is styled in a monospace font. The data source is an inline array of objects, and the rendering relies on D3’s SVG manipulation.

Rectangles using data Color

This example shows a set of seven colored rectangles, each labeled with a name, positioned at fixed coordinates on an SVG canvas. The rectangles are bound to an array of data objects containing x/y positions, dimensions, and color values. The code uses D3 v4’s `selectAll` and `data` binding to create and style each rectangle, then appends text labels next to them. The data comes from an inline JSON array, and the visualization uses SVG for rendering, with colors specified as hex and RGB strings.

75% match

Trying Squares

A grid of fifteen colored rectangles renders a fixed dataset of five values repeated three times, with each rectangle’s width proportional to its value and its fill assigned a random RGB color via the custom `getRandomColor` function. The React component uses `d3.sum` to compute total width and `d3.selectAll` to append SVG `rect` elements, while the `FaceContainer` wrapper translates the group into the SVG canvas. D3 v7 and React 18 combine to generate the static layout without interaction.

Ddumbdataguy@gmail.com

75% match

fresh block test

This example visualizes six colored rectangles positioned on an SVG canvas, with each rectangle’s dimensions and color defined by an array of JSON objects. It first calculates the maximum bounding box dimensions from the data using a for loop, then sets the SVG’s size accordingly. The code uses D3 v4’s selection and data binding methods (`d3.select`, `.data`, `.enter`) to append and style the rectangles via `.attr` and `.style` calls. The visualization highlights a simple approach to mapping raw data to geometric primitives, with the source data embedded directly in the script and rendering done entirely through SVG.