Abstract

The basic principles of `patterning' numerical data into tables are explained and illustrated with examples. The use of similarities between tables and graphs can help in visualizing the table's structural framework. Grouping information to bring out relationships can allow the significance of the data to be grasped more quickly by the reader. Other key requirements for clarity include 1) choosing concise, complete, and unambiguous headings and 2) eliminating redundancy.