Trying d3.enter and path

100%

Trying d3.enter and path

✓ Published0🌍 Public

Last edited Feb 6, 2020

Created on Feb 6, 2020

Forked from Making Vertical Bar chart with D3

This example demonstrates a simple scatterplot-like visualization of five data points, where each point is represented as a circle whose radius corresponds to its numeric value from the `mockData` array. The circles are positioned along the x-axis with their centers calculated cumulatively from the data values, and all are aligned at a fixed y-coordinate of 50. The visualization uses D3 v5's `select` and selection `.enter()` API to append SVG circle elements to a 500-pixel-high, 960-pixel-wide SVG canvas, with the circle's `cx` attribute derived from an offset loop and `r` bound directly to its data value. The data is hard-coded in the JavaScript rather than loaded from the provided `data.csv` file.

AI-generated description

MIT Licensed

Similar vizzes

Loading thumbnail…

Learn D3 in 5 minutes

This example shows how to create a simple scatterplot-like visualization using D3’s data join pattern. Five circles are bound to an array of numeric values, with each circle’s radius determined by its corresponding data point. The code uses `d3.select`, `.data()`, and `.join()` to bind the array, then applies inline SVG attributes for positioning and CSS styles for fill and stroke colors. Rendering occurs in an SVG element, with D3 v7 loaded via a CDN script tag.

PPremkumar

80% match

Loading thumbnail…

D3 Example

This example demonstrates a simple scatter plot where circular marks are placed on an SVG canvas based on data loaded from an external CSV file. The visualization shows how data points are bound to SVG circles, with their horizontal and vertical positions determined by the `x` and `y` properties of each data record. The code uses D3.js version 3.5.5, specifically the `d3.select`, `d3.csv`, and the `data`, `enter`, `update`, and `exit` selection methods to manage the circles. All circles are styled with a uniform teal fill (`#40E0D0`) and a fixed radius of 15 pixels, while the SVG viewport is set to 250 by 250 pixels. The rendering relies entirely on SVG elements.

AAlvaroMoro

79% match

Loading thumbnail…

fresh block

This example shows a simple scatterplot-style visualization of five circles, with each circle's position and color determined by its data value. The circles are placed horizontally and vertically based on the array `[25, 50, 125, 75, 100]`, and they turn purple when the value exceeds 100, otherwise yellow. The visualization uses D3 v4, selecting the body element, appending an SVG, and binding data with `selectAll` and `enter()`. Circle radii are fixed at 10, while `cx` and `cy` attributes derive directly from the data points, creating a one-dimensional distribution of distinct colored dots.

BBrieLewis

79% match

Loading thumbnail…

Fork of Circles with D3

This example shows a simple scatterplot of circles arranged on a 2D plane, with each circle’s position and size determined by explicit data values. It demonstrates D3’s data join and method chaining to bind an array of circle objects to SVG `<circle>` elements, setting `cx`, `cy`, `r`, and `fill` attributes. The visualization uses D3 v7 with the `select` function and the `.data().join()` pattern for efficient rendering, while the canvas background and opacity styling enhance the overlap effect. Data is embedded directly in the code as a static array, serving as a foundation for later loading external data sources.

RRohithNaiduDevareddy@my.unt.edu

78% match

Loading thumbnail…

D3 Example 1

This example plots five red circles on a light grey SVG canvas, with each circle’s position determined by x and y coordinates loaded from a tab-separated values file (`example1.tsv`). The visualization uses D3 v7, fetching the data via `d3.tsv()` and binding it to circle elements through `selectAll().data().enter().append()`. The circles are styled with fixed radius and fill color, while their `cx` and `cy` attributes are set directly from the data values, producing a simple scatterplot without any scales or axes.

OOleJRask

78% match

Loading thumbnail…

Check

This example demonstrates a scatterplot with five circles positioned on an SVG canvas, each sized according to a numerical value. The visualization is built using D3 version 7, specifically leveraging `select`, `scaleLinear`, `extent`, and the `axisLeft` and `axisBottom` helpers. The chart maps data from an inline array of objects with `xVal`, `yVal`, and `rVal` properties to positions and radii. The code uses the declarative scale functions to compute the mapping and appends the resulting circles to the SVG element, with the axes rendered at the left and bottom edges.

Fferneyhoughedward@gmail.com

78% match

Loading thumbnail…

D3.js

This example shows a scatterplot of population values from a CSV file, rendered as red circles on a black SVG canvas. It demonstrates basic data binding and enter/exit updates in D3 version 6, using `d3.select`, `d3.csv`, and `svg.selectAll` with `.enter()` and `.exit()`. The code initially positions circles using arbitrary random coordinates derived from each population value, then removes and re-adds a circle to illustrate update patterns. The positions do not correspond to meaningful axes, emphasizing the data-binding mechanics rather than accurate visualization.

IInnoFail

77% match

Loading thumbnail…

D3 Selection Exploration

This example demonstrates D3 selections and data joins by generating a row of 15 static circles across an SVG canvas. The visualization shows how `selectAll` combined with `data` and `enter` creates elements from an array of numbers. Using `d3.select` and `range`, it appends circles with a fixed radius and x-coordinate to the full-window SVG. The code relies on the core D3 selection API and SVG rendering, with no interaction or dynamic updates.

XXuân Vinh

77% match