A1c Chart

BArcharts of Insulin

This visualization displays horizontal bar charts showing the relationship between patient age and insulin levels, with the title "Diabeties level vs Age." The bars are sorted by age in descending order, with the x-axis representing age values (0–60) and the y-axis representing individual patient IDs based on their insulin measurements. The visualization uses D3 v6 APIs including `scaleLinear` for the age axis, `scaleBand` for the categorical insulin values, and SVG rendering. Data comes from a CSV file loaded via `d3.csv`, featuring diabetes patient records with insulin, glucose, and other health metrics.

VVineela Reddy

Vvedasrivarma13@gmail.com

line Chart

This line chart visualizes the relationship between age and the mean diabetes outcome, revealing how the average outcome varies across different ages. The data comes from a diabetes dataset loaded via `d3.csv` and processed with `d3.rollup` to calculate mean outcomes per age group. The visualization uses D3 v7’s `scaleLinear`, `axisBottom`, `axisLeft`, and `line` APIs within a React-compatible SVG rendering, styled with the Poppins font on a teal background. The chart includes rotated x-axis labels and axis titles for clarity.

Line Chart - Project 16

This line chart shows the relationship between BMI and average blood pressure for diabetes patients, with each line representing a distinct district and colored using an ordinal scale. The visualization uses d3.line with curveBasis for smooth path rendering, d3.scaleLinear for both axes, and d3.nest to group data by district. A custom colorLegend component displays the district categories, while axis labels and a title provide context. Data comes from a CSV file hosted on GitHub, and the chart is rendered as SVG using d3.v5.

Ggayuvurukuti@gmail.com

D3 Scatter Plot

This animated SVG scatter plot explores the Diabetes dataset, cycling through different x-axis variables (BMI, Glucose, Blood Pressure, Skin Thickness) every two seconds while displaying Glucose on the y-axis. Built with D3 v6, the reusable chart component uses `scaleLinear`, `extent`, and axis functions to render points. The code imports the dataset from a remote CSV URL, and the `setInterval` function drives the rotating axis animation.

AArun

Line Chart

This line chart visualizes monthly values for categories A through L, showing trends over time with a thick orange line connecting circular data points. The chart includes value labels and date labels for each point. Built with D3.js v3, it uses an ordinal x-scale, a linear y-scale, and SVG rendering. Hovering over a circle triggers a smooth transition that enlarges the point to yellow, reveals its corresponding value text, and draws a vertical orange line from the baseline, using D3's selection filtering and transition methods. The data comes from a local JSON file.

BBerengerCunillera

Scatter Plot - Project 16

This scatter plot visualizes a diabetes dataset, mapping glucose levels on the x-axis against BMI on the y-axis, with each point colored by outcome (red for positive, green for negative). It also encodes insulin and blood pressure values into the `rx` and `ry` attributes of the circles, creating elliptical markers. The visualization uses D3 v5 with SVG rendering, employing `scaleLinear`, `extent`, `axisLeft`, and `axisBottom` to construct the axes. Data is loaded asynchronously via `d3.csv` from a GitHub gist URL, with a custom row parser converting numeric fields.

Ggayuvurukuti@gmail.com

Avg Diabetic Age

This line chart displays the average age of diabetic individuals over a range of years. It uses the D3 v5 library, with `d3.scaleLinear` for both axes, `d3.axisBottom` and `d3.axisLeft` for tick marks, and `d3.line` with a basis curve to create a smooth path. The SVG rendering includes gridlines, axis labels, and a title, with data loaded from a CSV file via `d3.csv`. The line is styled green with three-pixel width in CSS.

SSUSHMA CHIRRA

Fork of Line Chart - Project 16

This visualization shows the relationship between glucose levels and BMI across countries, with each line representing a country's trajectory through the dataset. The chart uses a D3 line generator with curve basis to create smooth paths, scales from d3.scaleLinear for both axes, and d3.scaleOrdinal with schemeCategory10 for color encoding. Data is loaded from a CSV file using d3.csv, nested by country with d3.nest, and rendered as SVG. A custom colorLegend component displays the categorical color mapping.

Aav.dj.2000@gmail.com