We hope you enjoy our project! Thank you so much for all of your hard work and help, Tiffany!
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The files for this visualization are vis1.js and brain_disease_distribution.csv to illustrate the global distribution of major neurological conditions. I used different colors for each disease/condition to highlight its impact on the overall distribution of brain conditions and make sure it is easy to visually distinguish the different conditions. Additionally, there is a tooltip to highlight and specify the percentages for specific conditions to better understand the exact number breakdowns.
The files for this visualization are vis2.js and alzheimers_gender_data.csv. Through this data, I wanted to focus on both the racial and gender factors. I used two different colors to distinguish the genders for female and male. Additionally, with the axis titles, we are able to see the differnces for races based on the lengths of the bar charts. Since the bar chart lengths are very easy to distinguish it makes it easy for the user to understand the message of the chart. Additionally, the tooltip allows the user to better understand and interpret the data.
The files for this visualization are vis3.js, brain.jpg, and main.js. This visualization pulls data from a published estimate of Alzheimer's disease dementia in the 50 U.S. states and 3142 counties, which uses data from the Chicago Health and Aging Project and the 2020 bridged-race population estimates to calculate how many adults who are 65+ are living with Alzheimer's and what percent of older adults are affected in each state. I grouped the data into the 4 major U.S regions and each region is shown as a circle arranged on a cross. The size of each circle represents the number of cases per region and the color shows the regional prevalence (percent of adults 65+ with Alzheimer's). The tooltip appears on hover and shows the top states in that region by number of cases, so you can see how, for example, the Southern region have a the largest share of total cases.
The files for this visualization are worldMain.js, worldVis.js, countriesMSData.csv, and countries.geo.json. This visualization pulls data from the National MS Society, which has collected surveys from around the world to form 3 different data sets of multiple sclerosis based on years: 2008, 2013, and 2020/2022. I then simplified the data down to 3 different statistics: prevalence (number of total cases, standardized per 100,000 people), incidence (number of new cases, standardized per 100,000 people), and mean age of onset (average age that multiple sclerosis sets in). The user can both click on the dropdown menu above the map to select a statistic and a button below the map to select a different year, and the colors in the map will change accordingly based on the countries' data. There is a tooltip that appears when hovering over a country that tells the user of the specific country's data for that statistic.
The files for this visualization are heatmap.js, axes.js, aggregator.js, and MigraineMain.js. This visualization pulls data from nHanes, which is broad U.S. data that includes a lot of lifestyle and health data of U.S. citizens. It uses this to make a map that charts some conditions onto a grid by age and PHQ-9 (mental unwellness) score. So you can see how older, unhappy people might be impacted by chronic migraines more and then add in that they smoke or are divorced. The color is darker if more of the respondents who fit the conditions reported chronic migraines as well.
https://ayoun8.github.io/Final-project/
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