Finally I found a solution in the R language. The problem is that R language is not easy to learn. Similarly, if you don’t use it daily, it happens that most of the time you googling the solution. As a first step I created tool named FasteR (integrated development environment), which make easier R scripts writing. Consequently, as its iteration the Stagraph software was developed. In this case, the user has the same access via built-in console to all the functions of R runtime.
In Stagraph, manual typing of R scripts is only the second option to work with data. First of all, the program includes features that provide the principal functions in the form of a visual interface. User defines various activities with data visually and program generates for him R code automatically in the background. Using this interface, it is possible to import data, process, visualize and export the results. The program is therefore visual extension of the R language.
This architecture has some very interesting benefits. First, the program uses the power of open, statistically and numerically correct code that is tested, tuned and used by top leaders in the field of statistics, data science and data visualization. Here are limited errors which arise in the case of specific “black-box” solutions.
The program is based on functional language and its character deeply affects also the character of visual interface. If you don’t use ggplot2 until now for data visualization, you’ll be surprised how quickly and easily you can create very specific visualization. The program contains very few dialogues (settings) and still its use options are very large. In this program, we do not know the final number of graph types that can be created. Thanks to the “Grammar of Graphics” implementation by changing one simple parameter you can create a fundamentally different type of chart.
Until now, however, these functions were accessible mainly for those who are familiar with the R language. Stagraph now brings these features also to other users, without need for writing code. However, if you know the basics of R, the program brings you even more options, because as parameters you can set not only static object or value, but also R function.
The following video shows you a quick introduction to Stagraph program.
Next video demonstrating the potential of program in real practice. The examples are based mostly on environmental data from my practice.
If you want to compare Stagraph with the existing solutions, by architecture is probably the closest to the Tableau. The difference is that Tableau is currently in version 10.1 and Stagraph in version 1.0. Also different is their focus. Tableau is focused on business intelligence and Stagraph more on statistical graphics and deep visual data exploration.
The main motto of the program is: Luxury of ggplot2 visualizations for everyone.