R has a rich set of inbuilt features to visualize data using a range of chart types. In addition, R also has a range of visualization packages, such as ggplot2 that produce presentation grade graphics used in publications.
It is a common practice to visualize a dataset to understand the nature of the individual columns of data prior to beginning analysis. Not only does the visualization process shed light on the distribution of the data, but also the contents of the data at a high level.
Having a visual cue also helps in getting insights more rapidly, relative to having to analyze the data manually. Visualizations help to understand the following:
- Distribution of the data
- Presence of outliers
- Cardinality of the data
- Correlated variables
- Multivariate relationships
