Basic Scatter Plot

Basic Scatter Plot

This visualization uses D3 v4 to render a basic scatter plot of the Iris dataset, showing sepal length on the x-axis against petal length on the y-axis. The code employs `d3.scaleLinear` for both axes, `d3.axisBottom` and `d3.axisLeft` for tick marks, and SVG circles for data points. It also includes custom axis labels and uses `d3.csv` to load the remote Iris dataset, with data parsed by a row function that converts string values to numbers.

SShivaKarpe

96% match

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.

93% 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.

93% match

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

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 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.

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.

D3 Scatter Plot

This example visualizes the Iris Dataset as a scatter plot, mapping petal length to the x-axis and sepal length to the y-axis. Using D3 v6, it loads data via `d3.csv`, applies linear scales with `scaleLinear` and `extent`, and renders circles as marks. Axes are drawn with `axisBottom` and `axisLeft` in an SVG container. The plot fills the entire window and displays all 150 samples without color or categorical encoding.