task 8-part 3

Activity8_Task-3.2

This scatter plot displays iris flower measurements, plotting sepal length on the x-axis against petal length on the y-axis, with different species differentiated by shape markers and a legend. The visualization loads CSV data from a GitHub repository, parses it with `d3.csvParse`, and renders the chart using D3 v7’s `scaleLinear` and `scaleOrdinal` for scales, `symbolsFill` for shape encoding, and custom components for axes and shape legend. The plot utilizes `d3.select` and the join pattern to manage SVG elements dynamically, with the legend positioned at a fixed offset.

HHarika Metta

task-8(part-3)

This scatter plot visualizes the Iris dataset, showing petal length against petal width while color-coding points by species (setosa, versicolor, virginica). The code loads CSV data via `d3.csv`, scales the axes with `scaleLinear` and `extent`, and renders circles using `join`. Axes are drawn with `axisLeft` and `axisBottom`; the visualization uses the D3 v6 library and renders to SVG.

DDivyaKota2@my.unt.edu

Task8_task3-tutorial3.2

A scatter plot of Iris flower measurements maps sepal length against petal length, with species distinguished by symbol shapes and a custom legend. The visualization loads data from a GitHub-hosted CSV and renders marks using D3 v7. It demonstrates modularized code with `d3.scaleLinear`, `d3.scaleOrdinal`, `d3.symbol`, and custom axis and legend functions built from `d3.axisLeft` and `d3.axisBottom`.

Mmulyasuji999@gmail.com

Bbudalavijay2001@gmail.com

Activity6_Task3.2

This visualization displays a scatter plot of Iris flower measurements, plotting sepal length against petal length and encoding species using different symbol shapes. Each species appears as a distinct geometric marker with a corresponding legend positioned on the right. The code uses d3.scaleLinear for coordinate scaling, d3.scaleOrdinal with d3.symbolsFill for shape encoding, and d3.axisLeft/axisBottom for axes. Data is loaded asynchronously from a CSV file and parsed with d3.csvParse, while the scatter plot, axes, and legend are each structured as reusable D3 modules.

Mmanideepchinna25@gmail.com

Activity-8_Task-3.2

This example displays a scatter plot of Iris flower measurements, mapping sepal length and petal length onto x- and y-axes while encoding species identity through distinct point symbols. It loads CSV data from a GitHub repository using `d3.csvParse` and parses numeric columns before rendering. The visualization uses `d3.scaleLinear` for positioning, `d3.scaleOrdinal` with `schemeCategory10` for shapes, and custom SVG axes built from `d3.axisLeft` and `d3.axisBottom`. A custom legend component displays the species-to-shape mapping, and the code demonstrates modular ES6 imports across multiple local files with D3 v7.

Activity-8_task-3.2

This scatter plot displays iris flower measurements, mapping sepal length on the x-axis and petal length on the y-axis, with species encoded by symbol shapes shown in a custom legend. The visualization uses D3 v7 APIs including `scaleLinear` for axes, `scaleOrdinal` with `symbolsFill` for shape encoding, and `symbol` to generate the marks. Data comes from a CSV file parsed with `csvParse`, and the chart includes labeled axes and a separate shape legend positioned within the SVG.

Ttharunramula@gmail.com

Activity6_Task3.2

A scatter plot visualizes iris flower measurements, encoding sepal length on the x-axis, petal length on the y-axis, and species as categorical shapes. The code loads the iris dataset from a remote CSV, parses it with `d3.csvParse`, and renders the chart using D3 v7. Axes, shape legends, and SVG marks are generated with `d3.axisLeft`, `d3.axisBottom`, `d3.scaleLinear`, and `d3.symbol`.

SSahithi.R

Activity6Task3.2

This scatter plot displays Iris flower measurements, plotting sepal length against petal length for individual specimens. Each point’s shape encodes the species category, with a dedicated legend identifying the three species groups. The visualization loads the Iris dataset from a GitHub-hosted CSV file and parses it using `d3.csvParse`. It renders marks using the `d3.symbol` API with `symbolsFill` to generate different point shapes, while `d3.scaleLinear` and `d3.scaleOrdinal` handle positional and categorical scaling, and custom axes and legend components are assembled using D3 selections.

Gganesh.hns48@gmail.com