- authors: Mitchie Zhao, Jordon Lau, Kaicheng Tan, Daniel Ortiz
A data science project for DSCI 532 (Data Visualization II); a course in the Master of Data Science program at the University of British Columbia. You can find the reporting app here.
Alex is a policy maker working for the government of the United States. He wants to understand if mental health has become a major problem among employees from tech companies. He wants to be able to explore the Mental Health in Tech Survey dataset visually to compare the general situations of mental health issues for people in tech, both geographically and demographically, and find out the most relevant factors that can justify his intention to improve current labor contract policies.
The Mental Health in Tech Industry dashboard contains two tabs. The first "General Overview" tab is intended to give the user a broad glance at the prevalence of mental health conditions in the Tech sector. Users can analyze using the geographical map, age distribution histogram and a bar chart indicating if the condition interferes with their work. The second tab "Company Support" takes a deeper dive into tech worker perspectives' of their company's environment and culture towards dealing with mental health conditions. There are three plots under this tab: a boxplot for mental health consequences, a normalized bar chart for company support information, and a heatmap for discussion between coworkers and supervisors. Filtering options include a slider for age range selection, drop-down menus for state and company size, and options for filtering gender, tech company and remote work.
- altair==4.1.0
- dash==1.18.1
- dash-bootstrap-components==0.11.1
- pandas==1.1.5
- vega_datasets
- plotly==4.14.3
- gunicorn
