Exploratory Data Analysis of the Monkeypox Virus Using Machine Learning ^†

Abstract

The paper proposes the exploratory data analysis (EDA) of Monkeypox disease using machine learning approaches. Infection with the Monkeypox virus causes the uncommon illness of Monkeypox. The Monkeypox virus is a member of the Orthopoxvirus genus, which also includes the variola, vaccinia, and cowpox viruses that cause smallpox. To get the most out of the Monkeypox data, there is a need to perform some type of exploratory data analysis (EDA). This is a kind of data analysis that uses visual approaches to examine the data. Statistical summaries and graphical representations are used to detect trends and patterns, or to verify assumptions. In this paper, an exploratory data analysis of Monkeypox cases is performed using machine learning. Firstly, we find the top 10 countries based on confirmed cases, suspected cases, and hospitalized cases. Then, we find the cases with a travel history, cases without a travel history, confirmed Monkeypox cases across the globe, and suspected Monkepox cases across the globe. This will be very helpful for researchers working on machine learning and seeking patterns for Monkeypox to easily predict Monkeypox cases in their country.