Basic Scatter Plot

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.

94% match

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.

94% match

Basic Scatter Plot

This example shows a basic scatter plot of the classic Iris dataset, mapping sepal length to the x-axis and petal length to the y-axis. Each flower is rendered as a gray circle, with no color or shape encoding for species. The visualization uses D3 v4 within a React-style "margin" pattern, where a custom `d3.margin` function encapsulates the SVG margin convention. It loads CSV data with `d3.csv`, converts numeric fields, and positions circles using linear scales (`d3.scaleLinear`) over computed extents.

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.

Scatter Plot

This example visualizes the classic Iris dataset, displaying flower measurements in a scatter plot with points colored by species class. Each circle represents a single flower, positioned by its sepal and petal dimensions using D3’s `d3.scaleLinear` for x and y axes. The code loads data with `d3.csv`, appends SVG circles via `svg.selectAll` and `enter()`, and includes placeholder logic for axis rendering and hover tooltips. The visualization is rendered as an SVG within an HTML page, styled with external CSS, demonstrating basic D3 data-binding and scale patterns.

YYang Shun Yu

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.

Basic Scatter Plot

This scatter plot visualizes the Iris dataset, plotting sepal length against petal length for 150 iris flowers. The code uses D3 v4 to create an SVG visualization, employing `d3.scaleLinear` for both axes and `d3.axisBottom` and `d3.axisLeft` to render the axes. The data is loaded from a CSV file using `d3.csv`. Each flower is represented as a circle, with its position determined by the scaled values of the two measured dimensions.