adiag321 / suicide-rate-analysis

In this project, we have analyzed the Suicide Cases from 1985 - 2016 using Flourish and presented the findings with the help of Google Slides.

Suicide Rate Analysis (1985 - 2016)

PROJECT DESCRIPTION

From growing up in the heart of Silicon Valley, I have always wondered what was the factors that play a role in Suicide. There have been a plethora of suicide clusters from my High School in Palo Alto. This project seeks to explore the underlying factors. We will use a sample of 44,000 gather data from 141 different Countries, between the 80's to 2016. We would like to make a Machine Learning algorithm where we can train our AI to learn & improve from experience. Thus, we would want to predict the amount of suicides numbers in a certain demographic.

OVERVIEW

Data is collected from kaggle: https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016

In this mini-project, we will perform the following steps -

1. Data Wrangling
   
2. Exploratory Data Analysis
   
3. Machine Learning + Predictive Analytics
   
4. Conclusions
   
5. References
   

Finally, I have generated a report to present my findings to the audience using Google Sites- https://sites.google.com/view/suicide-rate-analysis

QUESTIONS FOR ANALYSIS

We will try to find the answers for the following questions during our analysis -

1. Which year has the most suicides cases? Which year has the least suicides cases?
2. Which country has the most suicides cases? Which country has the least suicides cases?
3. Is there any relation with Age groups and Number of Suicide cases?
4. What is the relationship between gender and the Number of suicides cases?

RESULTS

1. Population Pyramid

2. Age V/s Suicide Count

3. Country V/s Suicide Count

4. Suicide V/s Sex

5. GDP V/s Suicide

CONCLUSIONS

1. There was a decrease in suicides toward the '80s. This could be due to awareness of suicide & mental health in the 80s and improved recognition of those at risk. But shortly after that, there was a rise in suicides that we are seeing.
2. Russian levels of alcohol consumption play an immense role in its large suicide count, but there is a lack of data to support this due to Soviet secrecy.
3. The data illustrates that middle-aged adults between the ages of 30 through 60 have the highest suicide count. At the same time, the elderly and adolescents have about half the amount of middle-aged adults.
4. Suicide is one of the leading causes of death among all American adults. Data show alarming differences in suicide for different sexes. Males are more inclined to suicide than females. In addition, Mental health is a significant predictor of suicide.