Minimal 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.

Scatter Plot

This scatter plot visualizes the relationship between sepal length and petal width in the classic Iris dataset, which is loaded as CSV. The code uses D3 v7 scaleLinear and extent functions to map data to x and y pixel coordinates, and renders marks as SVG circles with an indigo fill. Axes are generated using axisBottom, axisLeft, and tick styling from Chivo Mono font, placed within a full-viewport SVG.

Wwaseemmedhat

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, 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.

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.

Scatter plot

This scatter plot displays the relationship between sepal length and sepal width for the Iris dataset. The visualization uses D3 v7 to load CSV data, compute scales with `scaleLinear`, and render SVG circles for each data point. Axes are generated using `axisLeft` and `axisBottom`, with margins and dimensions based on the browser window. The chart demonstrates a basic D3 workflow for plotting quantitative data from an external source.

NNUR UDDIN

Scatter plot

This scatter plot visualizes the Iris dataset, comparing sepal length and sepal width across 150 individual flowers. Each circle represents one sample, with its position determined by these two measured attributes while a green, semi-transparent fill makes overlapping points visible. The visualization is built using D3 v6, loaded via UNPKG, and rendered as SVG. Code imports functions like `scaleLinear`, `axisLeft`, and `axisBottom` from the D3 module to construct the axes and scales. Data is loaded from a local CSV file using D3’s `csv` method.

Wwei

Scatter Plot

This scatter plot displays the relationship between sepal length and sepal width in the Iris dataset, with each flower represented as a teal circle. The chart loads data from a CSV file using `d3.csv` and renders SVG circles via React components. Axes are built with `d3.scaleLinear` and custom tick components, while hover tooltips use the SVG `<title>` element to show formatted values.

Ppsabela