Community-level data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs; these graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. We developed MetacodeR, an R package for easily parsing, manipulating, and plotting hierarchical data. To accomplish this, MetacodeR provides a function to parse most text-based formats that contain taxonomic classifications, taxon names, taxon IDs, or sequence IDs. This parsed data can then be subset, sampled, and ordered using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function allows for the quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to color and size of tree nodes and edges. MetacodeR also allows exploration of barcode primer bias by integrating functions to run digital PCR. MetacodeR has been designed for data from metabarcoding research, but can easily be applied to any data that has a hierarchical component such as gene ontology, gene expression data, or geographic location data. Our package complements currently available tools for community analysis and is provided open source with extensive online user manuals.