Data classification is an essential part of research methodology and statistical analysis because raw data collected during research is usually large, diverse, and unorganized. Classification means arranging data into meaningful groups or categories according to common characteristics. It makes complex information easier to understand, compare, analyze, and interpret. Among the important methods of classifying data are geographical classification and chronological classification. Geographical classification organizes data according to place or geographical area, whereas chronological classification arranges data according to time or period. Both methods are widely used in social sciences, economics, business research, population studies, education, health research, and other fields. Geographical classification of data refers to the arrangement of observations according to their geographical location or area. The geographical basis may include countries, states, districts, cities, villages, regions, continents, climatic zones, rural and urban areas, or any other spatial unit relevant to the research. The main purpose of geographical classification is to identify differences and similarities among various locations. For example, a researcher studying literacy rates in India may classify the data according to different states such as Bihar, Jharkhand, Maharashtra, Kerala, Punjab, and Tamil Nadu. Similarly, information about agricultural production can be classified according to districts, while information about industrial development may be classified according to different regions or states. In business research, sales data can be classified according to geographical territories such as North India, South India, East India, and West India. Geographical classification is particularly useful when the geographical location is an important factor influencing the phenomenon under investigation. Natural resources, climate, population density, economic conditions, cultural practices, infrastructure, education, health facilities, and industrial development often vary from one geographical area to another. Therefore, geographical classification allows researchers to identify spatial variations. For instance, suppose a researcher wants to examine unemployment in different Indian states. The data may be arranged as follows: State A—8%, State B—6%, State C—10%, and State D—5%. Such an arrangement makes it easier to compare unemployment levels across states. The researcher can subsequently calculate averages, percentages, ratios, or other statistical measures for each geographical unit. Geographical classification can be based on different levels of spatial organization. At