In this project I aimed to use HTML and CSS to create a dashboard looking at global obesity rates and also look at obesity rates specifically in the US. I used matplotlib and pandas to generate the graphics and then used bootstrap within HTML to generate a responsive dashboard as well as using pandas df.to_html() command to include the raw data as a table inside of my website.
This is a screenshot of the landingpage outlining the aim of the dashboard and showcasing the increase in global obesity in males and females over time.
This screenshot shows the comparisons page showcasing all of the visualizations created for this dashboard. This page allows the user to get a quick snapshot of the analysis.
All ten of the nations in the top 10 Obese Nations are within the Oceanic region. Since the introduction of highly processed and calorie dense food in these regions, the rate of obesity has skyrocketed. Mining exploits in the past have drastically reduced the amount of arable land in these regions.
Since the late 70's global average obesity has been increasing drastically, with females outpacing males in rate of obesity. Due to the decreased costs of producing highly processed and calorie dense food as well as the increasing prevalence and ease of access to fast food it has been difficult for people to escape the cycle of obesity. With a heavier global populace come other health concerns such as increased rates of diabetes and cardiovascular diseases.
Similar to the rest of the world, the percentage of obese adults in the US has also been increasing at an alarming rate. The U.S. also has the highest cost of insulin in the world making it even more costly to individuals suffering from diabetes and obesity.
In recent years it looks like the rate at which obesity is increasing has fallen, possibly due to a larger push towards healthier eating.
This page holds the raw data that I used from kaggle to make the visualizaitons.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent