Untitled

100%

✓ Published0🌍 Public

Last edited Jun 26, 2022

Created on Jun 25, 2022

Forked from Fork of Fork of Fork of Rendering Data with React & D3

This interactive scatter plot displays the relationship between annualized standard deviation (x-axis) and annualized return (y-axis) for a dataset loaded via `d3.csv`. Each circle represents a data point, colored with `d3.scale.category20`, and features an SVG `<title>` tooltip showing the variable name and both metrics as percentages. Hovering triggers a smooth `d3.transition` that enlarges the circle and thickens its stroke. The visualization uses `d3.svg.axis` for both axes, with formatted tick labels and clear axis titles.

AI-generated description

A bare minimum HTML page demonstrating use of CSS and JavaScript.

Similar vizzes

Loading thumbnail…

Untitled

This interactive scatterplot explores yearly changes across seven data categories (A–G), displaying each category as a dot plotted along an ordinal x-axis of bars. Users navigate between years with left and right arrow keys, with an automatic playback feature advancing through the dataset. Built with React and D3.js v3, the visualization uses SVG rendering with `d3.scale.ordinal`, `d3.svg.axis`, and `d3.scale.category10` for color encoding. Data loads from an external CSV file, and the chart includes keyboard event handling and dynamic axis updates.

TThandolwethu Shakes Dlamini

82% match

Loading thumbnail…

Untitled

This interactive scatter plot displays three clusters of points, colored by category, and allows users to brush a region to zoom into that area. The visualization uses D3 v4 to generate data from a normal distribution, render SVG circles, and implement brushing with `d3.brush`. Axes are drawn with `d3.axisTop` and `d3.axisRight`, and zoom animations are handled via `svg.transition()`. The code also references a `data.csv` file with population figures, though the chart itself visualizes synthetic points.

Pprincit

80% match

Loading thumbnail…

Untitled

A scatter plot displays 100 randomly generated points within a fixed coordinate space. Each point is rendered as a red circle on an SVG canvas, with axes labeled from 0 to 500. The visualization uses D3 v4’s `d3.scaleLinear` for scaling, `d3.axisBottom` and `d3.axisLeft` to draw the axes, and appends circles via `selectAll` and `enter`. The data is synthetic, created with `Math.random` in a loop.

Ssaipaidipalli

79% match

Loading thumbnail…

Untitled

A scatter plot of the Iris dataset explores relationships between flower measurements. Dropdown menus allow selecting which attribute drives the x- and y-axes, using a linear scale for each. The visualization is built with React and D3, rendering SVG circles with tick marks and axis labels. Data is loaded asynchronously from a CSV via the `csv` function, and the chart updates dynamically based on user selections.

Ttmrb

78% match

Loading thumbnail…

Scatter Plot

This scatter plot visualizes the relationship between two numeric variables from a CSV dataset, plotting each point with x and y coordinates. It uses D3 version 6 with an SVG rendering approach, employing `d3.scaleLinear` to map the data domains to pixel ranges and `d3.axisBottom` and `d3.axisLeft` for the axes. Data is loaded asynchronously via `d3.csv`, and circles are appended and joined to the data using `.join('circle')`. The plot is styled with a teal fill and includes axis labels for "Numbers" and "Amount."

Bbugfree55

78% match

Loading thumbnail…

Untitled

This interactive scatterplot displays stock data with price on the x-axis and true value on the y-axis, using colored circles to represent stock types. Users filter the visualization through a dropdown menu for sector selection and jQuery UI sliders that adjust volume and delta ranges. The D3.js code loads data from a CSV file, applies keyed enter/update/exit selections, and includes hover tooltips that highlight individual stocks. The SVG renderer uses d3.axisBottom and d3.axisLeft for axes, with d3.scaleOrdinal for categorical coloring.

Mmkolowrat

78% match

Loading thumbnail…

Untitled

This example shows the annual variation of a single numeric value from 1895 to 2019, plotted as a time series using D3.js v6. The visualization calculates an SVG line chart from a CSV file with two columns, mapping the year to the x-axis and the value to the y-axis. The code loads the data with `d3.csv`, appends an SVG canvas with a fixed width and height, and prepares to render the dataset, though the drawing logic is incomplete. The chart relies on D3’s data-joining methods to bind the parsed rows to visual elements.

KKaitlyn Trudeau

78% match

Loading thumbnail…

Untitled

A temporal scatterplot displays circles representing entries from a CSV file, each positioned along a time axis based on parsed dates. A draggable slider with a play button animates through the timeline, revealing circles that grow in size upon entry. The visualization uses D3 v4 with SVG rendering, leveraging d3.scaleTime, d3.drag, and d3.csv to handle date parsing, slider interaction, and data loading within a React framework.

NNathanGBIM

78% match