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Vvandanakosuri@my.unt.edu
Last edited Apr 24, 2024
Created on Apr 24, 2024
Forked from task9(b)

This example shows an area chart of residual sugar measurements colored by wine quality, with the x-axis representing the row index in the dataset and the y-axis showing residual sugar values. The chart uses d3.area() to generate a single filled path in steelblue, with d3.scaleLinear for both axes and d3.axisBottom plus d3.axisLeft for tick marks. The SVG is rendered with D3 v7, rotating the x-axis labels to avoid overlap. The data is a static array of twenty objects with quality categories and residual_sugar values.

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task9(b)

This area chart visualizes residual sugar levels for wine samples categorized as “bad” or “good” quality. Using D3.js v7, an SVG path is filled via the `d3.area` generator, mapping each data point’s index to a linear x-scale and its sugar value to a y-scale. Axes are added with `d3.axisBottom` and `d3.axisLeft`, with rotated x-axis tick labels. The dataset is embedded directly in the script, and the chart is rendered with a steelblue fill on a 600×400 canvas, with margins and no external data source.

Vvandanakosuri@my.unt.edu
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Fork of Task 9 Question 2

This example visualizes the relationship between wine pH and total sulfur dioxide concentration as an area chart, with the area filled in steel blue and axes labeled accordingly. The chart filters data from a WineQT CSV hosted on GitHub, computed with D3's `d3.area` and `d3.scaleLinear`. It renders in SVG via D3 v6, using `d3.csv` for data loading, `d3.axisBottom` and `d3.axisLeft` for axes, and includes a legend rectangle. The accompanying text explains a comparison of machine learning models for stock volatility forecasting.

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Fork of ICE6.2 MBB

This example visualizes the relationship between residual sugar and citric acid in wine samples, with each point colored by wine quality category. It uses D3 v6 to load CSV data, create linear scales, and render circles in an SVG canvas. The code applies `scaleLinear` for both axes, `axisLeft` and `axisBottom` for ticks, and maps quality values to colors using a switch statement. The dataset is fetched from a remote CSV URL, and the visualization fills the full browser window with margins for labels.

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Task 9 Question 2

This example displays a filled area chart visualizing the relationship between pH and total sulfur dioxide in wine samples from the WineQT dataset. The chart emphasizes the so-called "area" between the pH values on the x-axis and the sulfur dioxide measurements on the y-axis, filled with steelblue. The code uses D3 v6 and builds the visualization with an SVG element. It employs `d3.scaleLinear` for both axes, the `d3.area` generator to create the path, and `d3.axisBottom` and `d3.axisLeft` for ticks and labels, alongside a legend and axis titles. Data is loaded from a CSV file hosted on GitHub.

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Fork of Activity6_Q

This scatter plot visualizes the red wine quality dataset, showing the relationship between fixed acidity and alcohol content. Each circle represents a wine sample, colored by its quality rating using a categorical color scale. The visualization uses D3 v6 APIs including `csv`, `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to load and parse the data, scale the values, and render the SVG axes and circles. The plot is responsive to the window size, with axis labels for both variables.

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Fork of Q 2 task 9 & 10

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Activity7-Q2

This area chart shows the relationship between wine quality scores and average alcohol content, using red wine quality data loaded from a GitHub-hosted CSV. The visualization aggregates the dataset by grouping wines according to their quality rating and calculating the mean alcohol percentage for each group, then renders this as a crimson, semi-transparent area path. The code uses D3 v7 APIs including `d3.csv` for data loading, `d3.rollups` and `d3.mean` for aggregation, `d3.area` for the shape, and `d3.axisBottom` and `d3.axisLeft` for the labeled axes.

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