Basic Scatter Plot

Basic Scatter Plot

This example shows a basic scatter plot of the Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis for 150 flowers. Using D3 v4, it loads the data from a CSV file with `d3.csv`, applies linear scales via `d3.scaleLinear`, and renders each flower as a circle element in an SVG container. The plot does not encode species or other dimensions, and includes no axes or labels.

95% match

Basic Scatter Plot

This example visualizes the classic Iris dataset, plotting sepal length against petal length for 150 flower specimens. Built with D3 v4, it loads data from a CSV file and uses linear scales with the margin convention to position circles in an SVG. The axis constraints are omitted, but the scatter plot effectively reveals the clustering of the three iris species based on their measured botanical dimensions.

94% match

Basic Scatter Plot

This example visualizes the classic Iris dataset, plotting sepal length on the x-axis against petal length on the y-axis for 150 flowers. The scatter plot uses semi-transparent circular marks colored by species, with a categorical color legend generated via the d3-legend plugin. Built with D3 v4, the visualization employs d3.scaleLinear for axes, d3.axisBottom and d3.axisLeft for ticks, and d3.scaleOrdinal with schemeCategory10 for color mapping. The SVG render includes labeled axes and a legend, with data loaded from a CSV file.

Basic Scatter Plot

This example visualizes the classic Iris dataset, plotting sepal length against petal length for 150 flowers of three species. Using D3.v4, it constructs an SVG scatter plot with labeled, ticked axes, employing `d3.scaleLinear`, `d3.axisBottom`, and `d3.axisLeft` for coordinate mapping and axis generation. The visualization also demonstrates custom axis label styling and margin-based layout, with data loaded from a CSV file.

D3 Scatter Plot

This example visualizes the Iris dataset as a scatter plot, mapping petal length on the x-axis and sepal length on the y-axis. Each flower is represented by a circle, with positions scaled linearly using d3.scaleLinear and extents from the data. The visualization renders in SVG, drawing circles directly onto an appended svg element. Axes are generated with d3.axisLeft and d3.axisBottom, styled with a 20px font size for tick labels. Data is loaded asynchronously using d3.csv from a remote Gist URL, with numeric parsing applied to all four measurement columns.

Ttverdone

D3 Scatter Plot

This example visualizes the Iris flower dataset as a scatter plot, mapping petal length to the horizontal axis and sepal length to the vertical axis. Each flower is rendered as a circle in an SVG canvas. The code loads CSV data using `d3.csv`, parses numeric fields, and applies linear scales via `d3.scaleLinear` with domains derived from `d3.extent`. Circles are joined to the data with `selectAll().data().join()`, sized with a fixed radius of 5 pixels, and positioned using the scaled coordinates.

Ttrongan765@gmail.com

Scatter Plot

This scatter plot visualizes the Iris dataset, displaying petal length against sepal length for individual flowers. The visualization uses React with D3 scales (`scaleLinear`, `extent`) to map data values to SVG coordinates, with custom axis components generating tick marks and labels. The D3 CSV loader fetches the data from a remote gist, while circles with 0.6 opacity represent each observation. The chart includes labeled axes and applies `nice()` to domain padding for cleaner tick intervals.

AAnkit5ingh

Basic Scatter Plot

This scatter plot visualizes the Iris dataset, plotting sepal length against petal length for 150 flowers. The code uses D3 v4 to create SVG circles, with axes customized via `d3.axisBottom` and `d3.axisLeft`, including negative tick sizes and padding. Data is loaded from a CSV file and parsed with a row function that converts measurements to numbers. Linear scales map the data domains to the plot dimensions, with a margin-based layout for the chart area.