data.tee, R’s package to handle tree structures, has grown a lot in popularity. In the three years since I first published on CRAN, it has been downloaded from RStudio mirrors alone more than 100’000 times.
See here to compare download statistics with other packages.
Also, there are 18 other CRAN packages that depend on data.tree, such as:
- ahp: my package to support multi-agent decision-making problems (it inludes a Shiny GUI, you can play around with it here).
- collapsibleTree: a widget to display interactive trees in Shiny
- sdcTable: a package used for statistical disclosure control, i.e. to balance the need to provide users with statistical outputs and the need to protect the confidentiality of respondents
- styler: a package to pretty-print R syntax
- …and many more
But data.tree is not only used as a low-level data structure for hierarchic data, but also as a tool to quickly plot trees. See here for examples of how to style your tree plots:
data.tree is “a bit different” and takes some getting-used-to for beginners. As a starting point, I recommend reading the sample applications vignette.
From the various consulting requests we get, we conclude that data.tree is also widely used in companies such as insurances, asset managers, and more.
Also, a big thank you goes to all the people that have supported the development of data.tree. Luckily, in some cases, we were able to pay back by involving the contributors as paid consultants in our consulting projects.
Goals? Well, think exponentially! How about a million downloads for the next three years? But then again, downloading numbers cannot be my main driver. Being able to provide a valuable tool to the R community will remain my main aspiration.