Basic Scatter Plot

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.

97% match

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.

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 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.

Basic Scatter Plot

This example visualizes the classic Iris dataset with a basic scatter plot, using D3 v4 to render circles in SVG that map sepal length and width. Each circle’s fill encodes the flower species via a color legend, generated with the d3-legend plugin. Axis ticks and labels are customized with scales, and the plot is fully responsive to the viewport.

94% match

D3 Scatter Plot

This D3 scatter plot visualizes the classic Iris dataset, plotting sepal length against petal length for 150 flower samples. Each circle represents an individual flower, with semi-transparent fill opacity to reveal overlapping points. The visualization is rendered as SVG, using d3.scaleLinear and d3.extent to map data values to screen coordinates, with axes generated via d3.axisLeft and d3.axisBottom. Data is loaded from a local CSV file using d3.csv, and the species of each sample is visible in the data but not encoded visually in this example.

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.