Lolipop Chart and KDE PLot
> The trend of gradual increase and sudden drop in suicidal deaths is same among the both genders.
> KDE Plot for representing density distribution of age and resident status.
> The dataset contains information on suicide fatalities in the USA spanning a 9-year period.
> It has 32 columns and 355667 entries.
> The dataset is not having data for 2012.
> February is having significantly less suicide fatalities than other months.
> However, May and July has more suicide fatalities than any other time in the year.
> The highest suicide incidents in the dataset occured in August and September 2014.
> 38.8% of the people who ended their life were high school graduates or GED complted.
> Higher education attainment is associated with notably lower rates of suicide.
> Dataset has 5 Maritial Statuses and 2 Genders.
> Men accounted for a significantly higher number of suicides among individuals of various marital statuses.
> Individuals who had maritial status as divorced, married, or have an unknown mostly ended their life between the ages of 40 and 60 years.
> Individuals who were never married or remained single took their own life at a comparatively younger age than those with other marital statuses.
> Lenght is one of the best visual perception of quantities.
> Lenght of Male thread reveals that Men are around 70%.
> The trend continues and among all maritial status Male are around 70%.
> Trend shows gradual increase of suicidal tragedies from 2005 till 2014, where it peaked with a saddening 43127 losses.
> Then number of sucidal deaths plummeted in 2015.
> The trend of gradual increase and sudden drop in suicidal deaths is same among the both genders.
> KDE Plot for representing density distribution of age and resident status.
> The majority of individuals who passed away by suicide were residents, making 86% of all.
> Interstate non-residents and foreign residents make up to a significant portion of the remaining 14% of fatalities.
> The number of Intrastate Non-residents is almost uniform among all years and is between 3000 to 4000.
> Similarly, the number of Interstate Non-residents is also somewhat uniform among all years, however trend for Residents is increasing steadily.
> Most individuals chose to spend their final moments at home.
> Even hospice and long-term care centers could not suffice the losses.
> The number of individuals till the age of 49 were significantly more with a difference of around 50,000.
> Seems a right skeewed chart, right ? Let's see what happens with more bins.
> Increasing the number of bins changes the perception of distribution of the data.
> More number of bins is making the distribution bi-modal now.
> The most number of count is for individuals aged between 48-51.
> We are using a more 'correct' approach where we are using density than count for determining the heights of the bars.
> With density, we are not being mislead about the distribution of the data.
> The age group 50-54 has the highest probabily according to this chart.
1. Perceptions of quantities - It can be observed particularly in the Sankey diagram, how easily Legth can be perceived.
2. Colorblind-friendly color schemes - We attempted to use the color scheme which is Colorblind-friendly and also maintained the same color scheme across all the plots.
3. Contrasting colors to reduce confusion - We used contrasting colors for better visual clarity.
4. We aimed to minimize the ink-to-data ratio, following Tufte's principle, and also strived to reduce clutter.
