What are data trees ?

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In Grasshopper, data trees are a fundamental data structure used to organize and manipulate data. A data tree is a hierarchical structure that allows for the storage and management of data in a nested manner. It provides a way to group and organize data into branches and sub-branches, similar to a tree structure.

In a data tree, each branch contains a collection of data items. These items can be numbers, points, vectors, curves, or any other data type used in Grasshopper. Each branch can have a different number of data items, and the branches themselves can have different lengths.

Data trees are particularly useful when working with multiple sets of data that need to be processed in parallel or when dealing with varying data structures within a single data set. They allow for the manipulation of data at different levels of granularity and facilitate operations that involve structured or nested data.

Data tree manipulation in Grasshopper involves accessing and modifying data at specific branch and item locations. Various components and techniques are available to work with data trees, such as "Split Tree," "Shift Paths," "Flatten," "Tree Statistics," and "Tree Branch." These components enable users to extract specific branches, merge or combine data from different branches, restructure data, and perform operations at different levels of the tree.

Understanding and effectively working with data trees is essential for advanced usage of Grasshopper, especially when dealing with complex algorithms, data management, and parametric design workflows. It allows for the organization, manipulation, and control of data in a structured and hierarchical manner, providing flexibility and control over the data flow within a Grasshopper definition.