Relationship Analysis between Suicide Rate & Happiness Report Indicators of a Country 2015-2016

• Used 3 datasets, GDP per Capita and Suicide rates for 2000, 2005, 2010, 2015 & 2016, World Happiness Report 2015, and World Happiness Report 2016. • Performed ETL to prepare the data to analysis, by removing columns, splitting datasets, merging the datasets using Python & Pandas library on Jupyter notebook • Applied descriptive analysis on suicide rates for 2015 & 2016 to have a bigger idea about the data using boxplot & exploring the top 5 countries for each year. • Created a correlation matrix using heat map using seaborn & Pandas libraries. • Created a function that will return a scatter plot with a regression line using seaborn library, the Pearson Correlation Coefficient, the p-value using stats from scipy, & returns if there is a correlation, if the correlation is negative or positive, if it is weak, moderate, strong, or very strong, and if it is significant or not • Visualized residual plots to confirm the possible correlations are linear relationship • https://github.com/Reemalraeai/Relationship-between-Suicide-Rate-and-Happiness-ReportFactors-of-the-Countries