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For example, June 30, 2001 is day 181 in the year 2001, as can be seen by adding 181 days to the date just before January 1, 2001. {{extract|June 30, 2001|show=dayofyear}} → 181 (date to day-of-year)
By default only the current version of a page is included. Optionally you can get all versions with date, time, user name and edit summary. Additionally you can copy the SQL database. This is how dumps of the database were made available before MediaWiki 1.5 and it won't be explained here further.
In communications messages, a date-time group (DTG) is a set of characters, usually in a prescribed format, used to express the year, the month, the day of the month, the hour of the day, the minute of the hour, and the time zone, if different from Coordinated Universal Time (UTC).
If a time zone designator is required, it follows the combined date and time. For example, "2007-04-05T14:30Z" or "2007-04-05T12:30−02:00". Either basic or extended formats may be used, but both date and time must use the same format. The date expression may be calendar, week, or ordinal, and must use a complete representation.
Panel data is the general class, a multidimensional data set, whereas a time series data set is a one-dimensional panel (as is a cross-sectional dataset). A data set may exhibit characteristics of both panel data and time series data. One way to tell is to ask what makes one data record unique from the other records.
Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record.
YAML (/ ˈ j æ m əl /, rhymes with camel [4]) was first proposed by Clark Evans in 2001, [15] who designed it together with Ingy döt Net [16] and Oren Ben-Kiki. [16]Originally YAML was said to mean Yet Another Markup Language, [17] because it was released in an era that saw a proliferation of markup languages for presentation and connectivity (HTML, XML, SGML, etc.).
The base data and the dimension tables are stored as relational tables and new tables are created to hold the aggregated information. It depends on a specialized schema design. This methodology relies on manipulating the data stored in the relational database to give the appearance of traditional OLAP's slicing and dicing functionality.