Skip to main content
100%

glucose

✓ Published0🌍 Public
Aalanmclean
Last edited May 9, 2014
Created on May 9, 2014

The visualization displays glucose measurements over time as white line paths and circular sample points, with one day highlighted in red via the currentDate class. It uses d3.csv to load Google Spreadsheet data, d3.nest to group records by date, and d3.scale.linear with d3.svg.line and cardinal interpolation to render each day’s trend across a 24-hour time axis. A dropdown menu, populated with unique dates, lets users switch the highlighted day. The SVG chart adapts to window size using jQuery width calculations, with axes and styling defined through CSS classes.

AI-generated description

Similar vizzes

Loading thumbnail…

sugar

This visualization displays daily blood glucose readings as multi-line time series, with each day’s measurements plotted against the time of day. A shaded horizontal band marks the target glucose range, while the most recent day’s line and points are highlighted in red. The code loads CSV data from a Google Spreadsheet via `d3.csv`, nests records by date using `d3.nest`, and renders SVG paths with `d3.svg.line` and cardinal interpolation. Circles mark individual glucose samples, and a dropdown menu populated by dates filters the highlighted series.

Aalanmclean
89% match
Loading thumbnail…

Glucose levels

This visualization displays glucose (blood sugar) measurements over time as a scatter plot, with each point representing a reading from a CSV dataset. The y-axis shows sugar levels, while the x-axis uses a time scale to map dates. A semi-transparent green band highlights the safe range between 70 and 140 mg/dL, allowing viewers to quickly identify readings outside the healthy zone. The chart supports interactive zooming and panning along the time axis, implemented via d3's zoom behavior, which re-renders the dots and safety band on changes. The y-axis is fixed, and the x-axis dynamically rescales as the user navigates through the time series data.

ZZJONSSON
81% match
Loading thumbnail…

Act 6.3

This scatter plot visualizes the relationship between Glucose and Insulin levels in a diabetes dataset, with red and green circles distinguishing diabetic and non-diabetic outcomes. It loads CSV data from a GitHub repository using d3.csv, then renders the plot as SVG with d3.scaleLinear, d3.axisLeft, d3.axisBottom, and d3.extent. The chart fills the browser window and includes labeled axes for Glucose and Insulin.

VVenkataSatyaRamKamini@my.unt.edu
74% match
Loading thumbnail…

activity6 task 3

This scatter plot visualizes the relationship between glucose and insulin levels in a diabetes dataset, with points colored red or green to indicate diabetic or non-diabetic outcomes. It loads CSV data from a GitHub repository using d3.csv, then applies d3.scaleLinear, d3.extent, d3.axisLeft, and d3.axisBottom to map the values. The chart renders as an SVG with circles positioned via cx and cy attributes, using window dimensions to size the plot responsively.

Ssiri2001j@gmail.com
74% match
Loading thumbnail…

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
72% match
Loading thumbnail…

Activity6_task3

This scatter plot visualizes the relationship between glucose and insulin levels in a diabetes dataset, with each point colored red or green to indicate the presence or absence of diabetes based on the Outcome variable. The visualization loads CSV data from a GitHub gist using D3’s `csv` method, then constructs linear scales with `scaleLinear` and `extent` to map the data to screen coordinates. It renders SVG circles for each data point, with axes created via `axisBottom` and `axisLeft`, and includes green axis labels for Glucose and Insulin.

Vvidiyalasahithi1999@gmail.com
72% match
Loading thumbnail…

Activity 9.2

This pie chart visualizes glucose levels for patients with diabetes, where each slice represents a patient and the slice’s size corresponds to their Glucose value. The chart includes a legend that pairs each patient’s BMI with their glucose level, and the slices are sorted by glucose in descending order. The visualization uses D3 v5 APIs including `pie`, `arc`, `scaleOrdinal`, and `schemeCategory10` to generate the SVG paths and color encoding. Data is loaded from a CSV file hosted on GitHub, and the chart is rendered within an SVG element on an HTML page.

Ss.harshinisai01@gmail.com
71% match
Loading thumbnail…

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
71% match