
For any number crunching work, be it making a report or developing a model or doing data diagnostics, visualization of the data is imperative. Be it univariate or multivariate data, visuals help us to look beyond the summary statistics or test statistics. For someone working in finance, there is an entire discipline of `Technical Trading’ where buy , sell , stop-loss decisions are made based on visuals. Whether one believes it or not is a different question altogether. Keeping Technical analysis side, there is an obvious need to look at data, be it histograms, density plots, contour plots, barplots, boxplots, etc. Tools that churn out these graphics are compulsory in any data analyst’s toolbox. My toolbox contains ggplot2, lattice and base-R. I had started using ggplot2 package, 4 years ago, and since then I have been using it regularly in my work. Since the output is usually publication ready, one of the real life situations where I had used ggplot2 visuals was in an annual newsletter to investors that reported their portfolio performance. I don’t think anybody cared about what the visuals were saying as long as the portfolio was making money. But using ggplot2 definitely lent a professional look to the newsletter.