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Activity 7.1 question 2

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SSiddhardha
Last edited Nov 8, 2024
Created on Nov 8, 2024
Forked from question 2

This example visualizes the distribution of petal length across iris species using a stacked area chart. It loads CSV data from a GitHub gist via D3’s `csv` method, then applies `scaleBand` for species categories and `scaleLinear` for petal length values. The chart uses `stack` and `area` generators to render a single filled area, with `axisBottom` and `axisLeft` for axes, and a title annotation. SVG output is produced through D3 selections.

AI-generated description

An example showing the capabilities of VizHub:

  • Loads D3 via UNPKG.
  • Demonstrates use of import from "d3".
  • Demonstrates use of import from local ES6 modules.
MIT Licensed

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question 2

This example displays petal length distribution across iris species using a stacked area chart. It loads data from a remote CSV file and renders an SVG visualization. The code imports D3 functions including `csv`, `scaleBand`, `scaleLinear`, `stack`, and `area`. It constructs an area generator with band scale positioning, adds axes via `axisBottom` and `axisLeft`, and labels the chart with a title. The visualization shows how petal lengths vary among species, with steelblue filling for the area.

Ppavithranamburi24@gmail.com
89% match
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Task8_Activity2

This example visualizes the distribution of petal lengths across three Iris species using a stacked bar chart with tooltips. The code loads data from a local CSV file and renders the chart as SVG using D3 v7. It employs `d3.stack()` to create stacked segments, `d3.scaleBand()` for the categorical species axis, and `d3.scaleLinear()` for the continuous petal length axis. Interactive mouseover events display tooltips showing the exact petal length for each species and segment.

Iikshwakalluri
85% match
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Activity-8_Question-2

This example visualizes the Iris dataset as a stacked bar chart, showing the relative contributions of sepal length, sepal width, petal length, and petal width for each of the three species. It uses d3.csv to load the data and d3.stack to transform the four numeric columns into stacked series. The chart renders as SVG with d3.scaleBand and d3.scaleLinear axes, and includes an interactive hover effect that increases bar opacity. A color-coded legend identifies each measurement category.

Hharipadmavathim2023@gmail.com
85% match
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activity7_question2

This stacked area chart visualizes the distribution of sepal width, petal length, and petal width across different sepal length values, using the classic Iris dataset. The chart shows how these three flower measurements contribute proportionally to the total across the range of sepal lengths, with color-coded categories shown in a legend. The visualization is built with D3.js (v7) and renders as an SVG, using `d3.stack()` for the stacked data, `d3.area()` for the area path generation, and `d3.scaleOrdinal()` for color mapping. The code reads data from a local CSV file and includes custom styling with fonts from Google Fonts.

Nnishwitha.1032@gmail.com
84% match
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Activity6Question2

This stacked bar chart visualizes the Iris dataset, showing the average measurements of sepal length, sepal width, petal length, and petal width for each of the three iris species. The code uses d3.csv to load the data, d3.stack to group the four numeric attributes into layers, and d3.scaleBand and d3.scaleLinear to map species and cumulative values. Rendered as SVG, each colored segment represents one measurement category, with axes added via d3.axisBottom and d3.axisLeft.

Nneerajreddyaluka@gmail.com
84% match
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Activity6_question3.1

This scatter plot visualizes the Iris dataset, showing the relationship between petal length and petal width, with each point colored by species (setosa, versicolor, or virginica). The chart uses D3 v6’s `csv`, `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to load data, scale axes, and render the SVG. Points are drawn as circles using D3’s `selectAll` and `join`, with axis labels styled in green. The data is fetched from a GitHub-hosted CSV file.

Kkandulasunny17@gmail.com
83% match
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activity6_question3

This visualization shows the Iris dataset as a scatter plot, mapping petal length on the x-axis and petal width on the y-axis, with points colored by species (setosa, versicolor, and virginica). Using D3 v6, it loads CSV data via `d3.csv`, scales the coordinates with `scaleLinear` and `extent`, and renders circles on an SVG canvas. It also includes axes via `axisLeft` and `axisBottom`, with inverted y-axis scaling and labeled axes. The code processes raw numeric fields—sepal and petal measurements—to position each data point.

Ddineshreddy.ravula@gmail.com
83% match
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Activity6-question3

This example displays a scatter plot of the Iris dataset, mapping petal length against petal width while color-coding points by species (skyblue, lightgreen, and orange). Data is loaded via `d3.csv` from a GitHub repository, and scales are created with `d3.scaleLinear` using `d3.extent`. The SVG circles are rendered with `d3.selectAll` and `.join`, while axes are added via `d3.axisLeft` and `d3.axisBottom`, with custom labels and styling.

Mmeenam1106@gmail.com
83% match