Florence Nightingale (1820-1910) is best known as a pioneer in modern nursing, but she was also a pioneer in statistics and the use of statistical graphics in data analysis. In her work during the Crimean War, she tended to the wounded soldiers in the hospitals and helped to improve the conditions in which they were treated. She collected data on patients and their outcomes, and used a coxcomb diagram to visually display the causes of death in soldiers. Nightingales coxcomb plot “Diagram of the Causes of Mortality in the Army in the East” illustrated that the main cause of death among the British troops in the Crimean War was preventable disease rather than injuries from fighting. The plot also shows that the death rate decreased when a Sanitary Commissioner arrived to aid in improving hygiene and sanitation. The coxcomb plot was later used by Nightingale to lobby for improved sanitation and hygiene in hospitals. This eventually led to a reduction in the death rate from disease in hospitals. She was a firm believer that statistical data presented as charts and diagrams is a powerful tool to make complex data more understandable. It help people see relationships between data and enables us to make informed decisions. I wanted to recreate Nightingales historical plot using R, and at the same time give a tutorial on “How to” make a coxcomb/polar-area plot/rose diagram