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This example visualizes cumulative minutes asleep for the top 23 users from a Fitbit sleep dataset, shown as multiple line series over time. Each line represents a user’s running total of sleep minutes, with end labels displaying user IDs and emphasis focusing on individual series on hover. Built with ECharts 5.3.2, the code loads a local CSV via `fetch`, parses rows to aggregate daily sleep records by user, and uses `myChart.setOption` to configure line charts, tooltips, legends, and an animated rendering with a 10-second duration.

79% match

Assignment 3 - Scatter on SingleAxis

This visualization shows the step counts for a single user across seven days of the week, using a series of scatter plots arranged on separate horizontal axes. Each point represents an hourly interval, with the x-axis showing the hour of the day and the size of the point scaled to the square root of the step count for that hour. The chart is built using the ECharts library, with each day’s data placed on its own `singleAxis` and rendered as a scatter series. The data is loaded from a local CSV file containing hourly step totals and intensity values.

79% match

Ssivaniammisetti2002@gmail.com

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This bar chart visualizes daily step counts over a 120-day period, with each bar representing one day and its height corresponding to the number of steps taken. The chart includes labeled axes for day and steps, plus a title, and uses axis ticks only for every tenth day to reduce clutter. The visualization loads CSV data via `d3.csv` from a GitHub gist, then uses `d3.scaleBand` for the x-axis and `d3.scaleLinear` for the y-axis. Bars are drawn as SVG rectangles using D3 v7's data join, with axes generated by `d3.axisBottom` and `d3.axisLeft`.

74% match

Assignment 3 - Scatter Plot with Linear Regression

This interactive visualization uses ECharts and the ecStat regression API to plot hourly step counts against calories burned for individual users from a Fitbit dataset. A dropdown menu switches between 33 users, each rendering a scatter plot with a linear regression line overlaid. The regression transform is applied via `ecStat.transform.regression`, while the chart itself loads data from a CSV file and updates dynamically through a change event listener.

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This workbench visualizes Fitbit user activity and sleep data, showing how daily metrics like step count, active minutes, and sleep efficiency cluster together. Users can toggle between different metrics and clusters to explore relationships in daily behavioral patterns. The interface uses D3.js v7 to render interactive SVG charts, including scatter plots and bar charts, alongside summary cards for key statistics. Data is parsed from a CSV file containing daily activity logs for multiple users, with filtering options for individual participants.

Ssivaniammisetti2002@gmail.com

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This scatter plot visualizes the relationship between daily step counts and calories burned, using a dataset loaded from a gist CSV. The chart, built with D3 v7, maps steps to the x-axis and calories to the y-axis via linear scales, rendering each data point as a small circle. It uses `d3.csv` to parse the data, `d3.scaleLinear` for axis scaling, and `d3.axisBottom` and `d3.axisLeft` to generate the axes, with a title and axis labels added as SVG text elements.

Assignment 3 - Interactive Stacked Bar Chart

This interactive stacked bar chart visualizes daily activity intensity for multiple users, sourced from Fitbit data in `dailyIntensities_merged.csv`. A dropdown menu switches between users, displaying four stacked segments—inactive, light, moderate, and intense activity—as proportions of a 1440-minute day. Built with ECharts 5.3.2, it uses the `bar` series with `stack: 'total'` for the bars, and adds translucent connecting polygons between adjacent bars via the `type: 'polygon'` element to highlight temporal transitions.