Data visualization is one of the most important tools to understand data for conveying information. Some important data visualization tools are describe here with the R codes. The following posts explain the methods needed for data visualization.
Creating a dashboard is an attractive way to visualize different groups of related data. To setup a dashboard we can use the R package flexdashboard.
First, setup the orientation of the dashboard in YML header. The default orientation is columns, which shows individual charts stacked vertically within each column. To setup the orientation row-wise specify orientation: rows option in YML header.
Similarly, we can display several components in different windows using a tabset.
The box plot is useful for comparing the quartiles and variation of quantitative variables. In a box plot, lower and upper ends of a box (the hinges) are the first (Q1) and third quartile (Q3), and the middle horizontal line represents the median (Q2) of the data. Outliers of the data are shown by the whiskers of the boxes, when data falls above 1.5 * IQR, where the inter-quartile range IQR = Q3 - Q1.