Exploratory Analysis and Forecasting of Suicides in India

Abstract

According to the National Crime Records Bureau (NCRB), in 2019, India reported an average of 381 deaths on a daily basis totalling to an alarming 1,39,123 fatalities[1]. Such appalling stats lead to an exigency in a thorough research of past trends and extrapolate information necessary to curb the dreadful act. Therefore, we propose a study, conducted on a dataset of over a period of 12 years in India, which includes intricate details regarding individual states, causes, means adopted, social status and various other concerns pertaining to the suicide rates. To depict trends as well as gain insights of the data with respect to factors like gender or states we have used Python libraries such as pandas, NumPy and seaborn for data pre-processing and Tableau for data visualisation. The results are sufficient to predict the cause for the increase in the rates and also prove as a notifier to the government as well as NGOs to avoid the tipping point. In addition to the above analysis, visualizations depicting a forecasting model have been added to predict the total cases in the upcoming years for some of the prominent states.