Vinay

Vinay Task 2

This scatterplot visualizes the relationship between petal length and petal width in the Iris dataset. Each purple circle represents a flower, with positions mapped by D3 linear scales on both axes. The visualization is built using React to manage the component lifecycle, while D3 v7 handles SVG rendering, axis generation, and data loading via `d3.tsv` from a GitHub gist. The chart includes labeled axes and a bold title, with circles styled with semi-transparency to reveal overlapping data points.

93% match

Fork of Vinay

A scatterplot shows the relationship between petal length and petal width for the Iris dataset, with each point colored purple and partially transparent. Built with React and D3 v7, the code loads tab-separated data via `d3.tsv`, then uses `d3.scaleLinear` and `d3.extent` to map values, `d3.axisBottom` and `d3.axisLeft` for axes, and appends SVG circles with x/y coordinates derived from the scaled data.

93% match

Vinay Task

This example uses a scatterplot to explore the relationship between petal length and petal width in the Iris dataset. It loads the data via `d3.tsv`, converts the numeric fields, and renders purple circles through the SVG-based D3 API. The chart uses `d3.scaleLinear` to map the continuous variables to the plotting area and displays them with `d3.axisBottom` and `d3.axisLeft`. Both axes are labeled, and a bold title describes the plot’s purpose. The visualization is built with React, which manages the container element, while D3 handles the SVG drawing.

92% match

vinay

This interactive scatter plot visualizes the Iris dataset, comparing sepal length and width across three iris species, with points colored by species and a legend that filters the data on hover. The visualization uses D3.js APIs including `scaleLinear`, `scaleOrdinal`, `axisBottom`, and `axisLeft` to render axes, scales, and circles, while the `ResizeObserver` enables responsive layout. The data is loaded directly from a CSV file via `d3.csv`, and the chart employs a custom BBC-style color theme defined in the theme configuration.

85% match

ic6 scattered plot

This visualization displays the Iris dataset as a scatter plot, encoding petal length on the x-axis and petal width on the y-axis, with each point colored by species (setosa in light green, versicolor in purple, and virginica in red). The code loads CSV data via `d3.csv`, parses numeric columns, and uses `d3.scaleLinear` with `d3.extent` to set the scales and `d3.axisLeft`/`d3.axisBottom` for the axes. It renders circles with SVG, though it also attempts to set `rx` and `ry` attributes (using sepal measurements) for each mark, a quirk that has no visual effect on circles. The chart is built in React with D3 v6, filling the browser window and labeling axes as "Petal length" and "Sepal length."

Ddivyagunuguntla

Activity 7 Scatter Plot

This scatter plot visualizes the Iris dataset, mapping petal length on the x-axis and petal width on the y-axis, with points colored by species (setosa, versicolor, and virginica) using skyblue, lightgreen, and orange. Built with D3 v6 in a React context, the code loads CSV data from GitHub, applies linear scales with `scaleLinear`, and renders SVG circles with attributes for x, y, fill, and radius. Axis labels appear in green text, and the plot resizes to fill the browser window using `window.innerWidth` and `window.innerHeight`.

BBhavanaGIrni

Vvinaykollapudi@my.unt.edu

tutorial3

This interactive scatter plot visualizes the Iris dataset, displaying petal length against petal width for individual flowers, with colors indicating species. Rendered as SVG, the plot uses D3 v6 functions including `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to map data coordinates and draw axes. Data is loaded asynchronously from a CSV file via `d3.csv`, and each point is rendered as a circle with a fixed radius, colored by species. The chart fills the browser window and includes styled axis labels.

Scatter Plot

This scatter plot displays the relationship between petal length and sepal width from the Iris dataset, with each point representing a flower sample. The visualization is rendered as an SVG using React components that leverage D3 v7 utilities for data loading and scaling. The code uses `scaleLinear` from D3 for both axes, `extent` to compute the domain from the data, and `csv` to parse the remote data source. Axis labels and tick marks are generated programmatically through reusable React components.

LLewis Ward