This report describes the approach and activities for the Data Sciences specialization Capstone project. The objective of the project is to develop a text prediction application like those used on mobile telephones and app’s like WhatsApp. This report covers the initial data analysis and high-level plans for the application

Part of the Coursera assignment for Building Data Products

Synopsis This data analysis looks at the severe weather events data of the U.S. National Oceanic and Atmospheric Administration’s (NOAA) storm database in the period from 1950 to 2011. The data contains information on fatalities and injuries as well as property and crop damages that resulted from severe weather conditions. The informations was grouped and aggregated to present the total health and total damage figures over the period of the most significant events. In this analysis it was considered to cluster the weather events based on the 48 standard NOAA weather event types, but a standard “pmatch” function together with small adjustments to improve the grouping of key events showed that our top 10 events covers well over 98% on the total victims and damages. Hence more sophisticated clustering was deemed unnecessary. Tornadoes, thunderstorms and excessive heat are the key causes of weather victims. While floods are the most significant cause of damage, followed by hurricanes and tornadoes.