Data can be represented graphically to make large and complex sets of information easier to understand, compare, and interpret. In Informetrics and Scientometrics, graphical representation is particularly useful for presenting publication trends, citation patterns, authorship productivity, journal performance, institutional output, and relationships among scientific publications. Different graphical methods highlight different characteristics of data. A bar graph is one of the simplest methods of graphical representation. It uses rectangular bars whose lengths are proportional to the values being represented. Bars may be arranged vertically or horizontally. A bar graph is useful for comparing discrete categories. For example, the number of publications produced by five departments in a university can be represented by separate bars for each department. Similarly, the number of articles published in different journals during a particular year can be compared through a bar graph. A histogram is used to represent the frequency distribution of continuous quantitative data. It consists of adjacent rectangular blocks, with the intervals of the variable shown on the horizontal axis and frequencies on the vertical axis. In Scientometrics, a histogram can show the distribution of citation counts among a group of research papers, such