Introduction
Data storage takes place in a variety of forms. The use of sparse matrices is a way to reduce the wastage of space which is a major disadvantage of the normal two dimensional storage systems. Data storage can also take place in lists. There are certain features that are common to the sparse matrices and lists as well as differences. This essay looks into similarities between the sparse matrices and lists.
Similarities between sparse matrices and lists
Data can be searched using various criteria both from sparse matrices and lists. In a sparse matrix, for example, a specific item is identified using the cell in terms of rows and columns. This can also be done to a list, though for a list, searching is mainly done using the row number. The difference only comes in the sense that sparse matrices are more complex than normal lists.
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"Data Storage".
Both the sparse matrices and lists contain data that can accessed directly. Sparse matrices are made up of rows and columns. Lists also have the columns that are occupied with data that can be obtained directly from looking at the data structure. Matrices are constructed from lists, and this lists supplements to them. One sparse matrix can contain more than two lists at the same time, which implies that it is just a more advanced method of data representation.
Both the sparse matrices and lists are used to give a synthesized information about a specific statistical record. Other than the similarities, there are certain key features that distinguish sparse matrices from ordinary lists.
Differences between Sparse Matrices and Lists
A sparse matrix is a special kind of matrix in which the rows and columns are pre-populated with zeros (Pai, 2008; 33). The non-zero values are displayed in a coordinate format. This is not the case in lists. For a list, the data spaces are empty before any data is fed into them. There are no pre-occupied cells, rows or columns.
The second difference comes in the sense that a sparse matrix is a system used mainly to store quantitative data. In the case of lists, data that is stored may take either the qualitative or quantitative form. This means that a list is more flexible to store many forms of information than a sparse matrix.
Even though the sparse matrix can be represented in the form of linked lists, it still remains to be a matrix which means that the data that is stored on it is capable of mathematical manipulation (Ngumi, 2014; 1). Basic mathematical operations such as multiplication can be done on a sparse matrix. Data that is represented on a list cannot be manipulated mathematically. This implies that the nature of the information is not in the format that allows for the basic arithmetic operations.
Sparse matrices can be modified to accommodate data from more sources since the non-occupied cells can be easily accessed. For a list, the storage is done in a specific order. Once occupied, there cannot be any additional information given. They may only be modified to match the expectations of the users.
A sparse matrix can be represented in different forms, for example in the form of a doubly linked list or in its initial form of rows and columns. This is not the case in a list. Most lists have conventional ways of representation, depending on the type of data to be represented. The information content dictates the size of the list and the nature of display that will be available on it.
Conclusion
Both the sparse matrices and lists are useful for data storage, but the type of information to be stored determines the more appropriate of the two methods.
- Ngumi, C. B (2014). Comparing the Sparse Matrix to List. From http://www.scribd.com/doc/62313765/Comparing-the-Sparse-Matrix-to-a-List
- Pai, G. A. V. (2008). Data structures and algorithms: concepts, techniques and applications. New Delhi, Tata McGraw-Hill.
