In this study, we develop high-dimensional representations of ions and assess their utility for materials informatics tasks. The SkipAtom 30 approach for developing distributed representations for the chemical elements is adapted to develop distributed representations of ionic species. We call our adapted formalism SkipSpecies. The SkipSpecies representation is then benchmarked in a structure-agnostic setting on two regression tasks (formation energy and band gap) and two classification tasks (metallic and magnetic classification) with differing dimension sizes, and different pooling operations. We find that ionic representations can perform better than standard element representations on tasks which are linked to the electronic structure of a material. A periodic table heatmap of the number of oxidation states available for each element in the dataset of 110,160 oxidation-state decorated structures obtained from the Materials Project. This figure was created using Pymatviz. implemented in Pymatgen (version: 2023.7.14) is used to query the oxidation states route of the database to obtain 154,718 non-deprecated structures.