Is Data Science Related to the Coronavirus?

Data Science and today’s hot topic, Coronavirus, may seem completely different from each other, but they are actually very correlated. Data Science can actually be used to map the Covid-19 outbreak, and gather information on it. To further explain, let’s go through the 4 steps of Data Science. First, Data Collecting. This is being done by the CDC and hospitals who are testing people for coronavirus and seeing who has it. This forms a data set, and there is all kinds of information about the patients, such as age, ethnicity, gender, and profession. Next, Data Wrangling comes into play when we eliminate some outliers to the data. For example, someone could have the common cold, and show similar symptoms to the coronavirus, but the positive test results could be inaccurate. With Data Wrangling, the outliers to the data set are removed. After that comes Data Analyzing, where a review of the data set is being done. From the current statistics, coronavirus mostly affects older people and those with underlying respiratory conditions. This can be inferred from the analysis of the data set, to see who is more at risk. Finally comes Data Representation. With representation, charts and maps of the coronavirus are being created, to inform people about who is most likely to get the virus. These maps also graphically show what areas the coronavirus is most common and spreading. This is also being done with the flatten the curve map, which is motivating people to stop the decline of the coronavirus.