Scatter plot testing

Scatter Plot

This scatter plot visualizes the Iris dataset, mapping petal length on the x-axis against sepal length on the y-axis. Using D3 v7, it loads CSV data via `d3.csv`, applies linear scales with `scaleLinear`, and renders circles as marks. Axes are drawn with `axisLeft` and `axisBottom`, and the SVG canvas fills the browser window. The code explicitly parses numeric fields and converts data values into pixel coordinates for each point.

SScott-Collier

93% match

D3 Scatter Plot

This D3 scatter plot visualizes the Iris dataset, mapping petal length on the x-axis and sepal length on the y-axis. The SVG rendering uses d3.scaleLinear to transform raw CSV values into pixel coordinates, with d3.min and d3.max defining the domains. Circles represent individual flowers, colored in a teal tone, while d3.axisLeft and d3.axisBottom generate labeled axes. The code loads data via d3.csv and appends text labels for both axes, using a full-window responsive layout with fixed margins.

Aainhoadieruiz@gmail.com

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, 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 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 visualization displays a scatter plot of the classic Iris dataset, mapping petal length on the x-axis against sepal length on the y-axis. The code loads the data using `d3.csv`, converts the numeric fields, and uses `d3.scaleLinear` with `d3.extent` to set the scales. Circles are rendered with `d3.selectAll` and `.join`, while `d3.axisLeft` and `d3.axisBottom` provide the labeled axes, with all drawing done in SVG.

SSam Hege

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.