A table plot is a simple thought powerful data visualization method that gives a quick summary of the variables (columns) of a table.
In this example, we visualize a table of data from a census taking place in a European country. The tool used to visualize it is an R package called tabplot.
The dataset is huge but we choose to visualize only some columns of such table. The columns we visualize are: Region name and the following three variables that are P1, P2, P3, P4, P5. Such variables correspond to P1 = total population, P2 = Male , P3 = Female, P4 = Married, P5= Single.
So given this dataset it is possible to have a quick summary of each column in a visual way. For example, it is possible to visualize it following these steps that are
a) loading the data and the R library
b) visualizing the Table plot
ds <- read.csv("censusdata.csv", sep = "\t", TRUE) install.packages("tabplot") library(tabplot) tableplot(ds, select = c(city,kind, age, size)) And this is the result. The advantage of such data visualization technique is that it gives the possibility to the analyst to note immediately for every variable i.e. column how it is related to the other variables. For example a region there can be more people married that in other regions. If you liked this guide show us your support. Comments and suggestions on how to improve our work are also welcome. And stay tuned, more guides on data visualization are coming.
