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Mental Health

✓ Published0🌍 Public
RRuba Khan
Last edited Sep 7, 2024
Created on Sep 2, 2024

This example visualizes the first record of a mental health survey dataset from Kaggle, showing parsed survey responses as a JSON string. The code loads `MentalHealthSurvey.csv` via a data import statement, then converts quantitative fields like age, CGPA, sleep hours, and Likert-scale ratings (depression, anxiety, isolation) from strings to numbers using unary plus and `parseFloat`. The parsed object is displayed in a `<pre>` element with a fixed font size, providing a quick reference for the data structure. The visualization relies on the CSV parsing and string interpolation in JavaScript, without additional libraries.

AI-generated description

The Mental Health Dataset, loaded and parsed as CSV.

Fork and modify this template to import your data to VizHub and export it for use in other vizzes! To do that:

  • Fork this viz
  • Clear out the README
  • Update the README with details about your dataset (including original source)
  • Replace data.csv with your own data
  • Replace the parsing logic in index.js with your own
  • Set the custom URL so you can import from it easily

Challenge

  • Find 3 datasets on a topic you are interested in
  • For each of those, fork this viz and replace the data
  • Parse the quantitative attributes into numbers
  • Update README.md to indicate the original data source

Analytics Task

  • I want to see if there is a correlation between average sleeping hours and GPA to understand the impact of sleep on academic success
  • I want to examine the distribution of residential status to see if it correlates with the feeling of isolation
  • I want to assess changes in depression and anxiety levels over the semester by comparing previous years' data to identify any shifts in student mental health
  • I want to look at the distribution of GPA among students in different degree majors to evaluate academic rigor of grading disparities across disciplines
  • I want to identify students with high academic pressure and financial concerns to target for university support services or financial aid programs
MIT Licensed

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