Part II - Combining Data

We have covered the basics of data visualization in plotting our Malaysian Covid data using points, lines, bars, pies, donuts, and columns. In Chapter 6 we combined lines and columns using two data frames in a single plot. But we mainly focused on working on one data frame with some data wrangling mainly using gather to convert the data frame to a long format and mutate to create new columns/variables. Only in Chapter 3 did we combine data frames using join.

Part II consists of three chapters. We will introduce maps as another powerful visualization tool. It is obvious that our data do not have maps. We need to get the map data and then integrate it with the Malaysian Covid data. This will involve quite a bit of data wrangling to combine data sets, where we have to format them properly and also recalculate data points if required. We will also see how to make compromises when we do not have all the data in the format that we require.

We will introduce network graphs as a data visualization tool in Chapter 9. There is a huge science in network graphs (thus the discipline is sometimes called Network Science) which we leave interested readers to explore separately. In this book, we borrow some of the concepts but focus on visualizing the network properties of the Malaysian Covid data when combined with maps. Again, it involves combining and reformatting data from various sources.

In Chapter 10, we explore the visual relationship of vaccinations, new cases, and deaths. We analyze the Malaysian data and also compare how we are doing with selected countries.

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