Mental Health Survey Pie Chart Project Momentum 4

100%

Mental Health Survey Pie Chart Project Momentum 4

✓ Published1🌍 Public

Last edited Nov 21, 2024

Created on Nov 21, 2024

Forked from Mental Health Survey Pie Chart Project Momentum 3

This interactive pie chart visualizes mental health survey data, showing average scores of selected well-being metrics across categorical attributes like academic year, gender, or university. Users filter the dataset using dropdown menus for attribute, metric, and university, with a reset button restoring defaults. The visualization uses D3.js’s `rollups` and `pie` functions to aggregate and generate arcs, while `arc` and `schemeCategory10` style the slices. Hovering reveals tooltips with precise values, and the chart reads from a local CSV file.

AI-generated description

An approximation of a line chart using D3.js!

Watch the video and study the code to learn about:

SVG Path Elements
fill, stroke, stroke-width
stroke-linecap, stroke-linejoin
Vanilla HTML SVG Paths
D3.line
AI Assist

Similar vizzes

Loading thumbnail…

Mental Health Survey Pie Chart Project Momentum 5

This interactive pie chart visualizes mental health survey data, showing the average of a selected metric (e.g., study satisfaction, anxiety) across categories of a chosen attribute (e.g., academic year, gender), with an optional filter for university. It uses the D3.js library to build the pie chart with the `pie` and `arc` generators, and employs `rollups` to compute group means. Dropdown menus and a reset button control the selections, while hover interactions display tooltips with the precise average value for each slice.

JJoe Rozman

97% match

Loading thumbnail…

Mental Health Survey Pie Chart Project Momentum 3

This interactive pie chart explores mental health survey data, letting users filter by university and toggle between demographic attributes and well-being metrics. The visualization displays average metric scores as proportional arc slices, with hover tooltips revealing exact values. Built with D3.js, it uses `d3.pie` and `d3.arc` to generate paths, `d3.rollups` for data aggregation, and `schemeCategory10` for color encoding. Dropdown menus control attribute, metric, and university selection, while CSS transitions provide visual feedback on hover.

JJoe Rozman

97% match

Loading thumbnail…

Mental Health Survey Pie Chart Project Momentum

This interactive pie chart explores mental health survey data, allowing users to select an attribute (such as academic year or gender) and a metric (like depression or anxiety) to visualize the average score across categories. The chart updates dynamically using D3’s pie and arc generators, with dropdown menus controlling the selections. Data is aggregated via rollups to compute mean values, and a color-coded legend displays each category’s label and average. The visualization uses the D3 library and is styled with custom CSS for the SVG and selector elements.

JJoe Rozman

96% match

Loading thumbnail…

Fork of Mental Health Survey Pie Chart Project Momentum Color

This interactive pie chart visualizes mental health survey data, showing how a selected metric (such as depression or academic pressure) varies across a chosen attribute like gender or academic year, filtered by university. Users adjust three dropdowns to explore different combinations. The visualization uses D3.js version 7.8.5, employing the `pie()` and `arc()` generators to create slices, `rollups()` for aggregation, and SVG elements for rendering. The code reads from the provided MentalHealthSurvey.csv file and updates the chart dynamically based on user selections.

JJoe Rozman

94% match

Loading thumbnail…

Mental Health Survey Pie Chart Project Momentum 2

This interactive pie chart visualizes mental health survey data from Pakistani universities, allowing users to explore how categorical demographics relate to self-reported well-being metrics. The visualization provides dropdown menus to filter by university, select a demographic attribute, and choose a psychological measure. The chart displays the average metric value for each category segment, with a legend showing labels and computed means. Built with D3.js version 7.8.5, the implementation uses the `pie` and `arc` functions from the d3-shape module, along with `rollups` for data aggregation and `schemeCategory10` for color assignment based on the CSV dataset.

JJoe Rozman

94% match

Loading thumbnail…

Mental Health Survey Pie Chart

This visualization shows the distribution of survey respondents across academic years using a pie chart, with each slice color-coded using `d3.schemeCategory10`. The code groups the mental health survey data by academic year through `d3.rollups`, sorts the categories, and renders the chart with `d3.pie` and `d3.arc` generators. A legend positioned at the top-right maps each color swatch to its corresponding academic year label. The SVG elements are sized dynamically to the container’s dimensions via `container.clientWidth` and `container.clientHeight`.

JJoe Rozman

90% match

Loading thumbnail…

Average Grade by Mental Health Status

This visualization shows the distribution of student anxiety levels as a pie chart, with each slice representing the proportion of students at a specific anxiety level. It uses d3.pie() and d3.arc() to render the pie, d3.scaleOrdinal() to assign colors, and d3.rollup() to count students in each anxiety category. Hovering displays a tooltip with the count and percentage, while clicking a slice populates a list of students in that anxiety level, showing their age, gender, sleep patterns, and stress levels. The data comes from a CSV file loaded via d3.csv().

Ddeekshakondam@gmail.com

78% match

Loading thumbnail…

Mental Health Survey Scatter Plot

This scatter plot visualizes the relationship between academic pressure and self-reported depression levels from a mental health survey dataset. Each circle represents a survey respondent, positioned according to their scores on these two variables, with a light gray background aiding readability. The visualization is built using D3.js, leveraging `scaleLinear` for axis scaling, `extent` to calculate data ranges, and custom axis label functions from the `@curran/axis-labels` library. The code imports the dataset from a `vizhub` reference and configures circles with a radius of 7.65 pixels and 62.9% opacity.

JJoe Rozman

77% match