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Anti-Grain Geometry (AGG) is a 2D rendering graphics library written in C++. It features anti-aliasing and sub-pixel resolution . It is not a graphics library, per se, but rather a framework to build a graphics library upon.
Oracle Database provides information about all of the tables, views, columns, and procedures in a database. This information about information is known as metadata. [1] It is stored in two locations: data dictionary tables (accessed via built-in views) and a metadata registry.
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license. [2]
In the context of Oracle Databases, a schema object is a logical data storage structure. [4] An Oracle database associates a separate schema with each database user. [5] A schema comprises a collection of schema objects. Examples of schema objects include: tables; views; sequences; synonyms; indexes; clusters; database links; snapshots ...
In database management, an aggregate function or aggregation function is a function where multiple values are processed together to form a single summary statistic. (Figure 1) Entity relationship diagram representation of aggregation. Common aggregate functions include: Average (i.e., arithmetic mean) Count; Maximum; Median; Minimum; Mode ...
Unfortunately there are a number of unsupported objects (e.g. tables or sequences owned by SYS, tables that use table compression, tables that underlie a materialized view or Global temporary tables (GTTs)) and unsupported data types (i.e.: datatypes BFILE, ROWID, and UROWID, user-defined TYPEs, multimedia data types like Oracle Spatial ...
In computing, a materialized view is a database object that contains the results of a query.For example, it may be a local copy of data located remotely, or may be a subset of the rows and/or columns of a table or join result, or may be a summary using an aggregate function.
Bootstrap aggregating, also called bagging (from bootstrap aggregating) or bootstrapping, is a machine learning (ML) ensemble meta-algorithm designed to improve the stability and accuracy of ML classification and regression algorithms. It also reduces variance and overfitting.