Table Manipulation Innovation
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Wikipedia
A table is an arrangement of information or data, typically in rows and columns, or possibly in a more complex structure. Tables are widely used in communication, research, and data analysis. Tables appear in print media, handwritten notes, computer software, architectural ornamentation, traffic signs, and many other places. The precise conventions and terminology for describing tables vary depending on the context. Further, tables differ significantly in variety, structure, flexibility, notation, representation and use. Information or data conveyed in table form is said to be in tabular format (adjective). In books and technical articles, tables are typically presented apart from the main text in numbered and captioned floating blocks.
A table consists of an ordered arrangement of rows and columns. This is a simplified description of the most basic kind of table. Certain considerations follow from this simplified description:
- the term row has several common synonyms (e.g., record, k-tuple, n-tuple, vector);
- the term column has several common synonyms (e.g., field, parameter, property, attribute, stanchion);
- a column is usually identified by a name;
- a column name can consist of a word, phrase or a numerical index;
- the intersection of a row and a column is called a cell.
The elements of a table may be grouped, segmented, or arranged in many different ways, and even nested recursively. Additionally, a table may include metadata, annotations, a header, a footer or other ancillary features.
The following illustrates a simple table with three columns and nine rows. The first row is not counted, because it is only used to display the column names. This is called a “header row”.
| First name | Last name | Age |
|---|---|---|
| Tinu | Elejogun | 14 |
| Javier | Zapata | 28 |
| Lily | McGarrett | 18 |
| Olatunkbo | Chijiaku | 22 |
| Adrienne | Anthoula | 22 |
| Axelia | Athanasios | 22 |
| Jon-Kabat | Zinn | 22 |
| Thabang | Mosoa | 15 |
| Rhian | Ellis | 12 |
The concept of dimension is also a part of basic terminology. Any “simple” table can be represented as a “multi-dimensional” table by normalizing the data values into ordered hierarchies. A common example of such a table is a multiplication table.
In multi-dimensional tables, each cell in the body of the table (and the value of that cell) relates to the values at the beginnings of the column (i.e. the header), the row, and other structures in more complex tables. This is an injunctive relation: each combination of the values of the headers row (row 0, for lack of a better term) and the headers column (column 0 for lack of a better term) is related to a unique cell in the table:
- Column 1 and row 1 will only correspond to cell (1,1);
- Column 1 and row 2 will only correspond to cell (2,1) etc.
The first column often presents information dimension description by which the rest of the table is navigated. This column is called “stub column”. Tables may contain three or multiple dimensions and can be classified by the number of dimensions. Multi-dimensional tables may have super-rows – rows that describe additional dimensions for the rows that are presented below that row and are usually grouped in a tree-like structure. This structure is typically visually presented with an appropriate number of white spaces in front of each stub’s label.
In literature tables often present numerical values, cumulative statistics, categorical values, and at times parallel descriptions in form of text. They can condense large amount of information to a limited space and therefore they are popular in scientific literature in many fields of study.
As a communication tool, a table allows a form of generalization of information from an unlimited number of different social or scientific contexts. It provides a familiar way to convey information that might otherwise not be obvious or readily understood.
For example, in the following diagram, two alternate representations of the same information are presented side by side. On the left is the NFPA 704 standard “fire diamond” with example values indicated and on the right is a simple table displaying the same values, along with additional information. Both representations convey essentially the same information, but the tabular representation is arguably more comprehensible to someone who is not familiar with the NFPA 704 standard. The tabular representation may not, however, be ideal for every circumstance (for example because of space limitations, or safety reasons).
A data manipulation language (DML) is a computer programming language used for adding (inserting), deleting, and modifying (updating) data in a database. A DML is often a sub language of a broader database language such as SQL, with the DML comprising some of the operators in the language. Read-only selecting of data is sometimes distinguished as being part of a separate data query language (DQL), but it is closely related and sometimes also considered a component of a DML; some operators may perform both selecting (reading) and writing.
A popular data manipulation language is that of Structured Query Language (SQL), which is used to retrieve and manipulate data in a relational database. Other forms of DML are those used by IMS/DLI, CODASYL databases, such as IDMS and others.
In SQL, the data manipulation language comprises the SQL-data change statements, which modify stored data but not the schema or database objects. Manipulation of persistent database objects, e.g., tables or stored procedures, via the SQL schema statements, rather than the data stored within them, is considered to be part of a separate data definition language (DDL). In SQL these two categories are similar in their detailed syntax, data types, expressions etc., but distinct in their overall function.
The SQL-data change statements are a subset of the SQL-data statements; this also contains the SELECT query statement, which strictly speaking is part of the DQL, not the DML. In common practice though, this distinction is not made and SELECT is widely considered to be part of DML, so the DML consists of all SQL-data statements, not only the SQL-data change statements. The SELECT ... INTO ... form combines both selection and manipulation, and thus is strictly considered to be DML because it manipulates (i.e. modifies) data.
Data manipulation languages have their functional capability organized by the initial word in a statement, which is almost always a verb. In the case of SQL, these verbs are:
Most SQL database implementations extend their SQL capabilities by providing imperative, i.e. procedural languages. Examples of these are Oracle’s PL/SQL and IBM Db2’s SQL_PL.
Data manipulation languages tend to have many different flavors and capabilities between database vendors. There have been a number of standards established for SQL by ANSI, but vendors still provide their own extensions to the standard while not implementing the entire standard.
Data manipulation languages are divided into two types, procedural programming and declarative programming.
Data manipulation languages were initially only used within computer programs, but with the advent of SQL have come to be used interactively by database administrators.