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Tables are a common way of displaying data. This tutorial provides a guide to making new tables and editing existing ones. For guidelines on when and how to use tables, see the Manual of Style. The easiest way to insert a new table is to use the editing toolbar that appears when you edit a page (see image above).
The process of converting a narrow table to wide table is generally referred to as "pivoting" in the context of data transformations. The "pandas" python package provides a "pivot" method which provides for a narrow to wide transformation.
Header cell, which can be column or row headers. Data cells are created with | Data cell. A new column can be added by adding another cell to the first row. To fill in the data for that column, add another data cell to the remaining rows. Spaces are ignored, thus | Data and |Data are identical.
Fact_Sales is the fact table and there are three dimension tables Dim_Date, Dim_Store and Dim_Product. Each dimension table has a primary key on its Id column, relating to one of the columns (viewed as rows in the example schema) of the Fact_Sales table's three-column (compound) primary key (Date_Id, Store_Id, Product_Id).
Note, in the above example, how the column-spacer of the 2nd column is set to only 9 spaces (compared to 13 on column 1), due to the text entries being longer words in column 2. In general, a set of 3 columns can each be spaced between 9-23 spaces apart, depending on wider column-spacers for shorter words in each column.
Each table is represented as a separate file in the destination directory, and there is a "data definition" file as well (a list of data definition declarations). During active use a log file appears in the active directory as well, and if the process crashes this log file is used to recover committed operations.
A wide-column store (or extensible record store) is a type of NoSQL database. [1] It uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row in the same table. A wide-column store can be interpreted as a two-dimensional key–value store. [1]
In a database, a table is a collection of related data organized in table format; consisting of columns and 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. [1]