Similarly, representation as a table implies a particular ordering to the rows and columns, whereas a relation is explicitly unordered. For instance, a SQL table can potentially contain duplicate rows, whereas a true relation cannot contain duplicate rows that we call tuples. In terms of the relational model of databases, a table can be considered a convenient representation of a relation, but the two are not strictly equivalent. The implementation consists of a list of arrays or vectors, each with a name. Conceptually, it is a list of records or observations all containing the same fields or columns. In many systems for computational statistics, such as R and Python's pandas, a data frame or data table is a data type supporting the table abstraction. External tables (in Informix įor example) can also be thought of as views. Views also function as relational tables, but their data are calculated at query time. The data in a table does not have to be physically stored in the database. Besides the actual data rows, tables generally have associated with them some metadata, such as constraints on the table or on the values within particular columns. "Table" is another term for "relation" although there is the difference in that a table is usually a multiset (bag) of rows where a relation is a set and does not allow duplicates. A specific choice of columns which uniquely identify rows is called the primary key. Each row is identified by one or more values appearing in a particular column subset. A table has a specified number of columns, but can have any number of rows. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect.
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