TableToLongForm automatically converts hierarchical Tables intended for a human reader into a simple LongForm Dataframe that is machine readable, hence enabling much greater utilisation of the data.
It does this by recognising positional cues present in the hierarchical Table (which would normally be interpreted visually by the human brain) to decompose, then reconstruct the data into a LongForm Dataframe. The article motivates the benefit of such a conversion with an example Table, followed by a short user manual, which includes a comparison between the simple one argument call to TableToLongForm, with code for an equivalent manual conversion. The article then explores the types of Tables the package can convert by providing a gallery of all recognised patterns. It finishes with a discussion of available diagnostic methods and future work.