World Happiness Report, a result of the Gallup survey rates the countries across the world based on their happiness index score. I have taken the results of 2019 from Kaggle Dataset which rates 156 countries happiness index scores along with their GDP per capita, social support, healthy life expectancy, freedom to make life choices, generosity and perception of corruption. How the survey was carried out is described here.
I have tried to look deeper into several questions from the data:
How does the happiness varies across countries of the world?
Do we become happy as we become richer and healthier?
How does the perception of corruption changes the happiness across the countries?
Do we become happy when we have social support?
The interactive visualization of the dataset below has 5 tabs. First 2 tabs answers the first 2 questions respectively. We really become happier as we get richer and healthier.
3rd and 4th tabs answer question no. 3. Here, we see something quite interesting. Perception of corruption among people does not have significant effect over happiness. People can think that corruption is prevailing in government and business sectors in their country, still they can be happy.
The last tab answers question no. 4 and it shows that we really become happier when we feel that we have social support. Finland, the country with highest happiness index score reports the highest social support.
In this data visualization project, I have used a dataset in Kaggle which has been prepared from WHOs mortality database online tool. We often hear that suicide rates are increasing throughout the world. How bad is it? Is it affecting everyone in the same way? In this analysis I have considered the timeline 1990-2010 and looked into several questions like:
How is the total number of suicides across countries of the world?
Is the suicide rate similar across different age groups and genders?
What is the trend in number of suicides in world?
Tab 1 below shows a map portraying the total number of suicides in different countries in the world. It also shows the change in them with time.
Tab 2 shows males are more prone to suicidal death than females. Moreover older people have suicidal deaths more than the younger people, which is even more evident when the data is normalized to the population.
Tab 3 shows that the total number in suicidal death is increasing both for males and females. However, the trend is steeper in case of males.
This project was done as a part of coursera's guided project: Building stock returns with Tableau. It shows the change in opening and closing price of stocks of some companies from tech, finance and medicine industries that are listed either in NYSE or NASDAQ. This heat map is colorized to the percentage change in stock prices on the day 12/4/2020 and sized to the market capitalization of the companies.